{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import copy\n",
    "from pprint import pprint\n",
    "import pandas as pd\n",
    "from pprint import pprint \n",
    "from scipy import stats\n",
    "import seaborn as sns\n",
    "import chardet\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#by chance, two people got the same mTurkCode of '6885935', we changed one  manually to '6885936' (already done)\n",
    "#we also needed to fix the UTF format of the file using 'iconv -f utf-8 -t utf-8 -c qualtrics_raw.csv > qualtrics_UTF.csv'\n",
    "#finally, manually fixed the platform names (i.e., space, spelling, not adding commas between the names .. they are few)\n",
    "\n",
    "#this is the very raw file after those changes (as exported by qualtrics)\n",
    "df = pd.read_csv('qualtrics_UTF.csv',index_col='mTurkCode')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>Initial file clean up (the structure, not content)</h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p>First of all, <strong>remove</strong> the duplicate title rows as they are exported by qualtrics (by default)</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>StartDate</th>\n",
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       "      <td>I wanted to maximize my own earnings</td>\n",
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       "      <td>Virginia, USA</td>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>CA, USA</td>\n",
       "      <td>21</td>\n",
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       "      <td>...</td>\n",
       "      <td>i dunno</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USA, wa</td>\n",
       "      <td>26</td>\n",
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       "      <td>Some college but no degree</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>9/13/17 15:01</td>\n",
       "      <td>9/13/17 15:03</td>\n",
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       "      <td>9/13/17 15:03</td>\n",
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       "      <td>...</td>\n",
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       "      <td>VA USA</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>Male</td>\n",
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       "      <th>3473940</th>\n",
       "      <td>9/13/17 16:32</td>\n",
       "      <td>9/13/17 16:34</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>152</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 16:34</td>\n",
       "      <td>R_QoFTmmuZ9XpSU4V</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>My son got tired of giving me money so he did ...</td>\n",
       "      <td>traits of AMT workers</td>\n",
       "      <td>PA, USA</td>\n",
       "      <td>52</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5269230</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>78</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>R_5hvlsH77FVdJIYh</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I work for myself, and don't want to give away...</td>\n",
       "      <td>Charitable behavior.</td>\n",
       "      <td>USA - Pennsylvania</td>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5077941</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>71</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>R_3k7kOJwgYHGeln9</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I wanted to make more money.</td>\n",
       "      <td>generosity and whether people will donate more...</td>\n",
       "      <td>Portland Oregon USA</td>\n",
       "      <td>25</td>\n",
       "      <td>female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6168759</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>86</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>R_AdPRLInN2cVd3nb</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>It's fair and equal.</td>\n",
       "      <td>I'm not sure.  Kindness?</td>\n",
       "      <td>USA, Michigan</td>\n",
       "      <td>30</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6634401</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>R_3fVGV5ZkNuTrHHl</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I wanted to maximize my own bonus.</td>\n",
       "      <td>To see how giving other people are.</td>\n",
       "      <td>California, USA</td>\n",
       "      <td>26</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>Over $100,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6026486</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>91</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_3ndW3UKWnJSDZjH</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Mturk had the most consistent money.  It was i...</td>\n",
       "      <td>Use of mturk vs willingness to give.</td>\n",
       "      <td>Rochester New York, USA</td>\n",
       "      <td>40</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1417422</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>108</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_22Etas0RSwBu4LT</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I have only had luck at mturk</td>\n",
       "      <td>charitable giving responses</td>\n",
       "      <td>USA, Maine</td>\n",
       "      <td>31</td>\n",
       "      <td>Male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5672286</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>93</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_sXpd178WWp5Pufv</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Mostly beneficial to me</td>\n",
       "      <td>generosity of an individual</td>\n",
       "      <td>Massachusetts, USA</td>\n",
       "      <td>32</td>\n",
       "      <td>male</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$80,001 - $100,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5755149</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>131</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_WCf8iglKqxhslH3</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I'm greedy.</td>\n",
       "      <td>Attitudes on generosity.</td>\n",
       "      <td>Texas, USA</td>\n",
       "      <td>25</td>\n",
       "      <td>Female</td>\n",
       "      <td>High school graduate</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>White,Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7287504</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>147</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_bjXB1zGjFGhHbRn</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>because I have worked for mturk since 2015</td>\n",
       "      <td>how people react to different questions</td>\n",
       "      <td>Colorado, USA</td>\n",
       "      <td>33</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6675635</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>163</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_22yanStURNkDQVi</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I like the idea of fairness and karma. I hope ...</td>\n",
       "      <td>What peoples' reasoning for dedicating or not ...</td>\n",
       "      <td>Michigan, USA</td>\n",
       "      <td>31</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7260435</th>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>67</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_CdY8ShpwrwFtgM9</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>i wanted the bonus</td>\n",
       "      <td>unsure</td>\n",
       "      <td>USA GA</td>\n",
       "      <td>22</td>\n",
       "      <td>male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5620933</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:37</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>175</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:37</td>\n",
       "      <td>R_242XSYOv1tLo5FX</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Money is tight for me right now but I normally...</td>\n",
       "      <td>If people are willing to share</td>\n",
       "      <td>USA, Maryland</td>\n",
       "      <td>27</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3010131</th>\n",
       "      <td>9/17/17 22:04</td>\n",
       "      <td>9/17/17 22:17</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>56</td>\n",
       "      <td>754</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_2947AC86K75R3j2</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8296099</th>\n",
       "      <td>9/17/17 22:20</td>\n",
       "      <td>9/17/17 22:22</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>56</td>\n",
       "      <td>151</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_22s2xF09Vvs197n</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4972910</th>\n",
       "      <td>9/18/17 0:27</td>\n",
       "      <td>9/18/17 0:28</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>48</td>\n",
       "      <td>80</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_1BXdXKFEhPPgfYN</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1945826</th>\n",
       "      <td>9/18/17 1:18</td>\n",
       "      <td>9/18/17 1:26</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>56</td>\n",
       "      <td>456</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_3MECPgZSFbAKkSu</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5037033</th>\n",
       "      <td>9/18/17 2:06</td>\n",
       "      <td>9/18/17 2:07</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>48</td>\n",
       "      <td>50</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_33Duo2nSnRAx7WK</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7666564</th>\n",
       "      <td>9/18/17 7:59</td>\n",
       "      <td>9/18/17 8:01</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>48</td>\n",
       "      <td>119</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_3fVpizHuyDIdLoG</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3626191</th>\n",
       "      <td>9/18/17 8:03</td>\n",
       "      <td>9/18/17 8:04</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>48</td>\n",
       "      <td>72</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_1LI3Ldd987I0Z5I</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5060255</th>\n",
       "      <td>9/18/17 9:51</td>\n",
       "      <td>9/18/17 9:58</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>48</td>\n",
       "      <td>427</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_2dQLQ9sRXGxqfTy</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2647 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               StartDate        EndDate      Status IPAddress Progress  \\\n",
       "mTurkCode                                                                \n",
       "2842236    9/13/17 11:11  9/13/17 11:12  IP Address   *******      100   \n",
       "4563666    9/13/17 11:11  9/13/17 11:12  IP Address   *******      100   \n",
       "6446494    9/13/17 11:11  9/13/17 11:13  IP Address   *******      100   \n",
       "5261906    9/13/17 11:12  9/13/17 11:13  IP Address   *******      100   \n",
       "5520318    9/13/17 11:11  9/13/17 11:13  IP Address   *******      100   \n",
       "2262834    9/13/17 11:11  9/13/17 11:14  IP Address   *******      100   \n",
       "8862928    9/13/17 11:11  9/13/17 11:14  IP Address   *******      100   \n",
       "2120472    9/13/17 11:11  9/13/17 11:14  IP Address   *******      100   \n",
       "5838413    9/13/17 11:13  9/13/17 11:15  IP Address   *******      100   \n",
       "1694952    9/13/17 11:11  9/13/17 11:15  IP Address   *******      100   \n",
       "3533894    9/13/17 11:14  9/13/17 11:16  IP Address   *******      100   \n",
       "7189868    9/13/17 11:21  9/13/17 11:22  IP Address   *******      100   \n",
       "5306294    9/13/17 11:31  9/13/17 11:35  IP Address   *******      100   \n",
       "8623697    9/13/17 11:39  9/13/17 11:41  IP Address   *******      100   \n",
       "8134166    9/13/17 15:01  9/13/17 15:03  IP Address   *******      100   \n",
       "8596815    9/13/17 15:06  9/13/17 15:08  IP Address   *******      100   \n",
       "6602150    9/13/17 16:12  9/13/17 16:15  IP Address   *******      100   \n",
       "3473940    9/13/17 16:32  9/13/17 16:34  IP Address   *******      100   \n",
       "5269230    9/13/17 20:34  9/13/17 20:35  IP Address   *******      100   \n",
       "5077941    9/13/17 20:34  9/13/17 20:35  IP Address   *******      100   \n",
       "6168759    9/13/17 20:34  9/13/17 20:35  IP Address   *******      100   \n",
       "6634401    9/13/17 20:34  9/13/17 20:35  IP Address   *******      100   \n",
       "6026486    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "1417422    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "5672286    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "5755149    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "7287504    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "6675635    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "7260435    9/13/17 20:35  9/13/17 20:36  IP Address   *******      100   \n",
       "5620933    9/13/17 20:34  9/13/17 20:37  IP Address   *******      100   \n",
       "...                  ...            ...         ...       ...      ...   \n",
       "3010131    9/17/17 22:04  9/17/17 22:17  IP Address   *******       56   \n",
       "8296099    9/17/17 22:20  9/17/17 22:22  IP Address   *******       56   \n",
       "4972910     9/18/17 0:27   9/18/17 0:28  IP Address   *******       48   \n",
       "1945826     9/18/17 1:18   9/18/17 1:26  IP Address   *******       56   \n",
       "5037033     9/18/17 2:06   9/18/17 2:07  IP Address   *******       48   \n",
       "7666564     9/18/17 7:59   9/18/17 8:01  IP Address   *******       48   \n",
       "3626191     9/18/17 8:03   9/18/17 8:04  IP Address   *******       48   \n",
       "5060255     9/18/17 9:51   9/18/17 9:58  IP Address   *******       48   \n",
       "5009844     9/18/17 9:40   9/18/17 9:43  IP Address   *******       56   \n",
       "7077643    9/18/17 11:04  9/18/17 11:06  IP Address   *******       56   \n",
       "7545990    9/18/17 21:26  9/18/17 21:27  IP Address   *******       44   \n",
       "8738901    9/18/17 16:01  9/18/17 16:02  IP Address   *******       56   \n",
       "2217859     9/18/17 7:45   9/18/17 7:46  IP Address   *******       48   \n",
       "8591661     9/18/17 8:39   9/18/17 8:39  IP Address   *******       44   \n",
       "5828228     9/18/17 8:07   9/18/17 8:20  IP Address   *******       56   \n",
       "4328917     9/18/17 8:45   9/18/17 8:51  IP Address   *******       56   \n",
       "1089141    9/18/17 10:40  9/18/17 10:42  IP Address   *******       48   \n",
       "4840647    9/18/17 12:23  9/18/17 12:25  IP Address   *******       48   \n",
       "6682723    9/18/17 12:27  9/18/17 12:29  IP Address   *******       56   \n",
       "3611286    9/18/17 21:07  9/18/17 21:08  IP Address   *******       48   \n",
       "3332819    9/21/17 21:24   9/22/17 8:18  IP Address   *******       48   \n",
       "4628194     9/18/17 7:56   9/18/17 7:59  IP Address   *******       48   \n",
       "5718227     9/18/17 7:45   9/18/17 7:46  IP Address   *******       44   \n",
       "5111805     9/18/17 8:12   9/18/17 8:15  IP Address   *******       48   \n",
       "5895146     9/18/17 0:31   9/18/17 0:31  IP Address   *******       48   \n",
       "8788125    9/18/17 21:43  9/18/17 21:45  IP Address   *******       56   \n",
       "1407579    9/18/17 21:06  9/18/17 21:08  IP Address   *******       56   \n",
       "2310788    9/18/17 12:34  9/18/17 12:34  IP Address   *******       48   \n",
       "4650666    9/18/17 12:36  9/18/17 12:38  IP Address   *******       56   \n",
       "7165602    9/18/17 12:39  9/18/17 12:40  IP Address   *******       56   \n",
       "\n",
       "          Duration (in seconds) Finished   RecordedDate         ResponseId  \\\n",
       "mTurkCode                                                                    \n",
       "2842236                      51     TRUE  9/13/17 11:12  R_vqUgiL0RrIcUZaN   \n",
       "4563666                      47     TRUE  9/13/17 11:12  R_a2A6STjMB7b7LnH   \n",
       "6446494                     112     TRUE  9/13/17 11:13  R_3JwUGrCtLZRT0M0   \n",
       "5261906                      86     TRUE  9/13/17 11:13  R_2Y6f8YlWkL9eYfm   \n",
       "5520318                     133     TRUE  9/13/17 11:13  R_1mwRKmTWSfljrTR   \n",
       "2262834                     138     TRUE  9/13/17 11:14  R_6gRQdDFJJLce1JT   \n",
       "8862928                     160     TRUE  9/13/17 11:14  R_3EEI6vysVLsXxJS   \n",
       "2120472                     168     TRUE  9/13/17 11:14  R_yCmJjtveHIVLkf7   \n",
       "5838413                      89     TRUE  9/13/17 11:15  R_2SH0dL8FYg4ocr5   \n",
       "1694952                     233     TRUE  9/13/17 11:15  R_3EW2IwQIa8KqtRv   \n",
       "3533894                      82     TRUE  9/13/17 11:16  R_ZI7cF6ge94QYSKR   \n",
       "7189868                      78     TRUE  9/13/17 11:22  R_1kRzX8PSoNw2USA   \n",
       "5306294                     256     TRUE  9/13/17 11:35  R_3lAohlIOjmfX3k5   \n",
       "8623697                     126     TRUE  9/13/17 11:41  R_3hDRkTVTxO1olmd   \n",
       "8134166                     113     TRUE  9/13/17 15:03  R_s6V4HtdE4qD17t7   \n",
       "8596815                     112     TRUE  9/13/17 15:08  R_232EPK2fUxbl77l   \n",
       "6602150                     152     TRUE  9/13/17 16:15  R_1eKp3z27TvT7WQi   \n",
       "3473940                     152     TRUE  9/13/17 16:34  R_QoFTmmuZ9XpSU4V   \n",
       "5269230                      78     TRUE  9/13/17 20:35  R_5hvlsH77FVdJIYh   \n",
       "5077941                      71     TRUE  9/13/17 20:35  R_3k7kOJwgYHGeln9   \n",
       "6168759                      86     TRUE  9/13/17 20:35  R_AdPRLInN2cVd3nb   \n",
       "6634401                      75     TRUE  9/13/17 20:35  R_3fVGV5ZkNuTrHHl   \n",
       "6026486                      91     TRUE  9/13/17 20:36  R_3ndW3UKWnJSDZjH   \n",
       "1417422                     108     TRUE  9/13/17 20:36  R_22Etas0RSwBu4LT   \n",
       "5672286                      93     TRUE  9/13/17 20:36  R_sXpd178WWp5Pufv   \n",
       "5755149                     131     TRUE  9/13/17 20:36  R_WCf8iglKqxhslH3   \n",
       "7287504                     147     TRUE  9/13/17 20:36  R_bjXB1zGjFGhHbRn   \n",
       "6675635                     163     TRUE  9/13/17 20:36  R_22yanStURNkDQVi   \n",
       "7260435                      67     TRUE  9/13/17 20:36  R_CdY8ShpwrwFtgM9   \n",
       "5620933                     175     TRUE  9/13/17 20:37  R_242XSYOv1tLo5FX   \n",
       "...                         ...      ...            ...                ...   \n",
       "3010131                     754    FALSE  9/24/17 21:22  R_2947AC86K75R3j2   \n",
       "8296099                     151    FALSE  9/24/17 21:22  R_22s2xF09Vvs197n   \n",
       "4972910                      80    FALSE  9/24/17 21:22  R_1BXdXKFEhPPgfYN   \n",
       "1945826                     456    FALSE  9/24/17 21:22  R_3MECPgZSFbAKkSu   \n",
       "5037033                      50    FALSE  9/24/17 21:22  R_33Duo2nSnRAx7WK   \n",
       "7666564                     119    FALSE  9/24/17 21:22  R_3fVpizHuyDIdLoG   \n",
       "3626191                      72    FALSE  9/24/17 21:22  R_1LI3Ldd987I0Z5I   \n",
       "5060255                     427    FALSE  9/24/17 21:22  R_2dQLQ9sRXGxqfTy   \n",
       "5009844                     204    FALSE  9/24/17 21:22  R_1Q61p15frP3k8V6   \n",
       "7077643                      89    FALSE  9/24/17 21:22  R_2tAwrH0I6fYwlPs   \n",
       "7545990                      20    FALSE  9/24/17 21:22  R_eeQIUTZmfaInKp3   \n",
       "8738901                      94    FALSE  9/24/17 21:22  R_24iszkMRqf1L6ri   \n",
       "2217859                      53    FALSE  9/24/17 21:22  R_3kM52bPemSgNj7S   \n",
       "8591661                      29    FALSE  9/24/17 21:22  R_2AF0gEcEsNe2ClT   \n",
       "5828228                     761    FALSE  9/24/17 21:22  R_BxFldZ7wDPsgJ45   \n",
       "4328917                     354    FALSE  9/24/17 21:22  R_3FOFg7mX859fnFX   \n",
       "1089141                     158    FALSE  9/24/17 21:22  R_voF5rzmFWHGI6GJ   \n",
       "4840647                     124    FALSE  9/24/17 21:22  R_1GObuCyWlIy6Zvl   \n",
       "6682723                     174    FALSE  9/24/17 21:22  R_2xQ1MwDPb9ymnoI   \n",
       "3611286                      34    FALSE  9/24/17 21:22  R_sBDh2yPwc6qnvUt   \n",
       "3332819                   39215    FALSE  9/24/17 21:22  R_1FP2WxQNP8jrEEp   \n",
       "4628194                     188    FALSE  9/24/17 21:22  R_25zJaKjkdgDKZty   \n",
       "5718227                      20    FALSE  9/24/17 21:22  R_1g79UNYJPz6QwdC   \n",
       "5111805                     175    FALSE  9/24/17 21:22  R_0V8oMQ0d6vA0M0N   \n",
       "5895146                      55    FALSE  9/24/17 21:22  R_22y3QXmhxvkYD6s   \n",
       "8788125                     152    FALSE  9/24/17 21:22  R_3EG1D3SZHHq0Y44   \n",
       "1407579                      98    FALSE  9/24/17 21:22  R_3qU05gXnBr8vMV7   \n",
       "2310788                      42    FALSE  9/24/17 21:22  R_3iBWq356sut7DSm   \n",
       "4650666                     117    FALSE  9/24/17 21:22  R_21z9OVauxE9qFF3   \n",
       "7165602                      83    FALSE  9/24/17 21:22  R_3ezr0xwCUGGllMI   \n",
       "\n",
       "          RecipientLastName        ...         \\\n",
       "mTurkCode                          ...          \n",
       "2842236             *******        ...          \n",
       "4563666             *******        ...          \n",
       "6446494             *******        ...          \n",
       "5261906             *******        ...          \n",
       "5520318             *******        ...          \n",
       "2262834             *******        ...          \n",
       "8862928             *******        ...          \n",
       "2120472             *******        ...          \n",
       "5838413             *******        ...          \n",
       "1694952             *******        ...          \n",
       "3533894             *******        ...          \n",
       "7189868             *******        ...          \n",
       "5306294             *******        ...          \n",
       "8623697             *******        ...          \n",
       "8134166             *******        ...          \n",
       "8596815             *******        ...          \n",
       "6602150             *******        ...          \n",
       "3473940             *******        ...          \n",
       "5269230             *******        ...          \n",
       "5077941             *******        ...          \n",
       "6168759             *******        ...          \n",
       "6634401             *******        ...          \n",
       "6026486             *******        ...          \n",
       "1417422             *******        ...          \n",
       "5672286             *******        ...          \n",
       "5755149             *******        ...          \n",
       "7287504             *******        ...          \n",
       "6675635             *******        ...          \n",
       "7260435             *******        ...          \n",
       "5620933             *******        ...          \n",
       "...                     ...        ...          \n",
       "3010131             *******        ...          \n",
       "8296099             *******        ...          \n",
       "4972910             *******        ...          \n",
       "1945826             *******        ...          \n",
       "5037033             *******        ...          \n",
       "7666564             *******        ...          \n",
       "3626191             *******        ...          \n",
       "5060255             *******        ...          \n",
       "5009844             *******        ...          \n",
       "7077643             *******        ...          \n",
       "7545990             *******        ...          \n",
       "8738901             *******        ...          \n",
       "2217859             *******        ...          \n",
       "8591661             *******        ...          \n",
       "5828228             *******        ...          \n",
       "4328917             *******        ...          \n",
       "1089141             *******        ...          \n",
       "4840647             *******        ...          \n",
       "6682723             *******        ...          \n",
       "3611286             *******        ...          \n",
       "3332819             *******        ...          \n",
       "4628194             *******        ...          \n",
       "5718227             *******        ...          \n",
       "5111805             *******        ...          \n",
       "5895146             *******        ...          \n",
       "8788125             *******        ...          \n",
       "1407579             *******        ...          \n",
       "2310788             *******        ...          \n",
       "4650666             *******        ...          \n",
       "7165602             *******        ...          \n",
       "\n",
       "                                                    strategy  \\\n",
       "mTurkCode                                                      \n",
       "2842236                                         I want money   \n",
       "4563666                 I wanted to maximize my own earnings   \n",
       "6446494                                 I want my max bonus.   \n",
       "5261906                                              i dunno   \n",
       "5520318                 Give something back to the platform    \n",
       "2262834    I was sick of working for other people who did...   \n",
       "8862928                                     for extra income   \n",
       "2120472                    I didn't want to destroy anything   \n",
       "5838413    I don't know the other person and I might need...   \n",
       "1694952    I needed extra money since I am a student and ...   \n",
       "3533894    I was not sure how legitimate it was so i gave...   \n",
       "7189868                    I wanted to maximize my earnings.   \n",
       "5306294    From what I have seen in most studies no one g...   \n",
       "8623697    There is no reason or incentive to give the bo...   \n",
       "8134166    I'm a greedy bastard, so my natural inclinatio...   \n",
       "8596815                                         I need money   \n",
       "6602150                I don't think there is another person   \n",
       "3473940    My son got tired of giving me money so he did ...   \n",
       "5269230    I work for myself, and don't want to give away...   \n",
       "5077941                         I wanted to make more money.   \n",
       "6168759                                 It's fair and equal.   \n",
       "6634401                   I wanted to maximize my own bonus.   \n",
       "6026486    Mturk had the most consistent money.  It was i...   \n",
       "1417422                        I have only had luck at mturk   \n",
       "5672286                              Mostly beneficial to me   \n",
       "5755149                                          I'm greedy.   \n",
       "7287504           because I have worked for mturk since 2015   \n",
       "6675635    I like the idea of fairness and karma. I hope ...   \n",
       "7260435                                   i wanted the bonus   \n",
       "5620933    Money is tight for me right now but I normally...   \n",
       "...                                                      ...   \n",
       "3010131                                                  NaN   \n",
       "8296099                                                  NaN   \n",
       "4972910                                                  NaN   \n",
       "1945826                                                  NaN   \n",
       "5037033                                                  NaN   \n",
       "7666564                                                  NaN   \n",
       "3626191                                                  NaN   \n",
       "5060255                                                  NaN   \n",
       "5009844                                                  NaN   \n",
       "7077643                                                  NaN   \n",
       "7545990                                                  NaN   \n",
       "8738901                                                  NaN   \n",
       "2217859                                                  NaN   \n",
       "8591661                                                  NaN   \n",
       "5828228                                                  NaN   \n",
       "4328917                                                  NaN   \n",
       "1089141                                                  NaN   \n",
       "4840647                                                  NaN   \n",
       "6682723                                                  NaN   \n",
       "3611286                                                  NaN   \n",
       "3332819                                                  NaN   \n",
       "4628194                                                  NaN   \n",
       "5718227                                                  NaN   \n",
       "5111805                                                  NaN   \n",
       "5895146                                                  NaN   \n",
       "8788125                                                  NaN   \n",
       "1407579                                                  NaN   \n",
       "2310788                                                  NaN   \n",
       "4650666                                                  NaN   \n",
       "7165602                                                  NaN   \n",
       "\n",
       "                                             experimentAbout  \\\n",
       "mTurkCode                                                      \n",
       "2842236                                            who cares   \n",
       "4563666                                         I don't know   \n",
       "6446494    To see how much people are willing to help oth...   \n",
       "5261906                                                  NaN   \n",
       "5520318                                          Perception    \n",
       "2262834                                     I have no idea.    \n",
       "8862928                                             not sure   \n",
       "2120472                                       I have no idea   \n",
       "5838413                                          Generosity    \n",
       "1694952                                           Not sure.    \n",
       "3533894                                      our generosity.   \n",
       "7189868    How people think about what they feel in certa...   \n",
       "5306294                                            Morality    \n",
       "8623697    Whether people are likely to give money away t...   \n",
       "8134166                  I think it's studying human greed.    \n",
       "8596815                                                greed   \n",
       "6602150                                         I'm not sure   \n",
       "3473940                                traits of AMT workers   \n",
       "5269230                                 Charitable behavior.   \n",
       "5077941    generosity and whether people will donate more...   \n",
       "6168759                             I'm not sure.  Kindness?   \n",
       "6634401                  To see how giving other people are.   \n",
       "6026486               Use of mturk vs willingness to give.     \n",
       "1417422                          charitable giving responses   \n",
       "5672286                          generosity of an individual   \n",
       "5755149                             Attitudes on generosity.   \n",
       "7287504              how people react to different questions   \n",
       "6675635    What peoples' reasoning for dedicating or not ...   \n",
       "7260435                                               unsure   \n",
       "5620933                       If people are willing to share   \n",
       "...                                                      ...   \n",
       "3010131                                                  NaN   \n",
       "8296099                                                  NaN   \n",
       "4972910                                                  NaN   \n",
       "1945826                                                  NaN   \n",
       "5037033                                                  NaN   \n",
       "7666564                                                  NaN   \n",
       "3626191                                                  NaN   \n",
       "5060255                                                  NaN   \n",
       "5009844                                                  NaN   \n",
       "7077643                                                  NaN   \n",
       "7545990                                                  NaN   \n",
       "8738901                                                  NaN   \n",
       "2217859                                                  NaN   \n",
       "8591661                                                  NaN   \n",
       "5828228                                                  NaN   \n",
       "4328917                                                  NaN   \n",
       "1089141                                                  NaN   \n",
       "4840647                                                  NaN   \n",
       "6682723                                                  NaN   \n",
       "3611286                                                  NaN   \n",
       "3332819                                                  NaN   \n",
       "4628194                                                  NaN   \n",
       "5718227                                                  NaN   \n",
       "5111805                                                  NaN   \n",
       "5895146                                                  NaN   \n",
       "8788125                                                  NaN   \n",
       "1407579                                                  NaN   \n",
       "2310788                                                  NaN   \n",
       "4650666                                                  NaN   \n",
       "7165602                                                  NaN   \n",
       "\n",
       "                          location  age     sex  \\\n",
       "mTurkCode                                         \n",
       "2842236                        USA   25    male   \n",
       "4563666              Virginia, USA   27    Male   \n",
       "6446494                    CA, USA   21    Male   \n",
       "5261906                    USA, wa   26  female   \n",
       "5520318               USA Indiana    29    Male   \n",
       "2262834             Wisconsin, USA   35    Male   \n",
       "8862928                     USA TN   49  Female   \n",
       "2120472                        USA   38  female   \n",
       "5838413                    MO, USA   26  female   \n",
       "1694952                    WA, USA   21  Female   \n",
       "3533894              USA Wisconsin   30    male   \n",
       "7189868                    USA, PA   36    male   \n",
       "5306294                Vermont USA   44   Male    \n",
       "8623697                    OH, USA   30    male   \n",
       "8134166                     VA USA   25    Male   \n",
       "8596815                     USA PA   27    male   \n",
       "6602150                    NY, USA   27    Male   \n",
       "3473940                    PA, USA   52  female   \n",
       "5269230         USA - Pennsylvania   27    Male   \n",
       "5077941        Portland Oregon USA   25  female   \n",
       "6168759              USA, Michigan   30  Female   \n",
       "6634401            California, USA   26    Male   \n",
       "6026486    Rochester New York, USA   40    Male   \n",
       "1417422                 USA, Maine   31    Male   \n",
       "5672286         Massachusetts, USA   32    male   \n",
       "5755149                 Texas, USA   25  Female   \n",
       "7287504              Colorado, USA   33  Female   \n",
       "6675635              Michigan, USA   31  Female   \n",
       "7260435                     USA GA   22    male   \n",
       "5620933              USA, Maryland   27  female   \n",
       "...                            ...  ...     ...   \n",
       "3010131                        NaN  NaN     NaN   \n",
       "8296099                        NaN  NaN     NaN   \n",
       "4972910                        NaN  NaN     NaN   \n",
       "1945826                        NaN  NaN     NaN   \n",
       "5037033                        NaN  NaN     NaN   \n",
       "7666564                        NaN  NaN     NaN   \n",
       "3626191                        NaN  NaN     NaN   \n",
       "5060255                        NaN  NaN     NaN   \n",
       "5009844                        NaN  NaN     NaN   \n",
       "7077643                        NaN  NaN     NaN   \n",
       "7545990                        NaN  NaN     NaN   \n",
       "8738901                        NaN  NaN     NaN   \n",
       "2217859                        NaN  NaN     NaN   \n",
       "8591661                        NaN  NaN     NaN   \n",
       "5828228                        NaN  NaN     NaN   \n",
       "4328917                        NaN  NaN     NaN   \n",
       "1089141                        NaN  NaN     NaN   \n",
       "4840647                        NaN  NaN     NaN   \n",
       "6682723                        NaN  NaN     NaN   \n",
       "3611286                        NaN  NaN     NaN   \n",
       "3332819                        NaN  NaN     NaN   \n",
       "4628194                        NaN  NaN     NaN   \n",
       "5718227                        NaN  NaN     NaN   \n",
       "5111805                        NaN  NaN     NaN   \n",
       "5895146                        NaN  NaN     NaN   \n",
       "8788125                        NaN  NaN     NaN   \n",
       "1407579                        NaN  NaN     NaN   \n",
       "2310788                        NaN  NaN     NaN   \n",
       "4650666                        NaN  NaN     NaN   \n",
       "7165602                        NaN  NaN     NaN   \n",
       "\n",
       "                                       education                 Q32  \\\n",
       "mTurkCode                                                              \n",
       "2842236    Bachelor's degree in college (4-year)   $25,001 - $35,000   \n",
       "4563666               Some college but no degree   $15,001 - $25,000   \n",
       "6446494     Associate degree in college (2-year)   $15,001 - $25,000   \n",
       "5261906               Some college but no degree        under $5,000   \n",
       "5520318    Bachelor's degree in college (4-year)   $65,001 - $80,000   \n",
       "2262834    Bachelor's degree in college (4-year)   $25,001 - $35,000   \n",
       "8862928               Some college but no degree  $50,001 -  $65,000   \n",
       "2120472               Some college but no degree   $65,001 - $80,000   \n",
       "5838413                     High school graduate   $25,001 - $35,000   \n",
       "1694952               Some college but no degree        under $5,000   \n",
       "3533894    Bachelor's degree in college (4-year)  $80,001 - $100,000   \n",
       "7189868    Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "5306294     Associate degree in college (2-year)   $25,001 - $35,000   \n",
       "8623697     Associate degree in college (2-year)   $15,001 - $25,000   \n",
       "8134166    Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "8596815    Bachelor's degree in college (4-year)    $5,000 - $10,000   \n",
       "6602150               Some college but no degree  $50,001 -  $65,000   \n",
       "3473940               Some college but no degree   $10,001 - $15,000   \n",
       "5269230                          Master's degree   $25,001 - $35,000   \n",
       "5077941    Bachelor's degree in college (4-year)   $10,001 - $15,000   \n",
       "6168759               Some college but no degree   $15,001 - $25,000   \n",
       "6634401    Bachelor's degree in college (4-year)       Over $100,000   \n",
       "6026486    Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "1417422     Associate degree in college (2-year)   $65,001 - $80,000   \n",
       "5672286                          Master's degree  $80,001 - $100,000   \n",
       "5755149                     High school graduate   $10,001 - $15,000   \n",
       "7287504               Some college but no degree  $50,001 -  $65,000   \n",
       "6675635               Some college but no degree    $5,000 - $10,000   \n",
       "7260435               Some college but no degree   $25,001 - $35,000   \n",
       "5620933               Some college but no degree    $5,000 - $10,000   \n",
       "...                                          ...                 ...   \n",
       "3010131                                      NaN                 NaN   \n",
       "8296099                                      NaN                 NaN   \n",
       "4972910                                      NaN                 NaN   \n",
       "1945826                                      NaN                 NaN   \n",
       "5037033                                      NaN                 NaN   \n",
       "7666564                                      NaN                 NaN   \n",
       "3626191                                      NaN                 NaN   \n",
       "5060255                                      NaN                 NaN   \n",
       "5009844                                      NaN                 NaN   \n",
       "7077643                                      NaN                 NaN   \n",
       "7545990                                      NaN                 NaN   \n",
       "8738901                                      NaN                 NaN   \n",
       "2217859                                      NaN                 NaN   \n",
       "8591661                                      NaN                 NaN   \n",
       "5828228                                      NaN                 NaN   \n",
       "4328917                                      NaN                 NaN   \n",
       "1089141                                      NaN                 NaN   \n",
       "4840647                                      NaN                 NaN   \n",
       "6682723                                      NaN                 NaN   \n",
       "3611286                                      NaN                 NaN   \n",
       "3332819                                      NaN                 NaN   \n",
       "4628194                                      NaN                 NaN   \n",
       "5718227                                      NaN                 NaN   \n",
       "5111805                                      NaN                 NaN   \n",
       "5895146                                      NaN                 NaN   \n",
       "8788125                                      NaN                 NaN   \n",
       "1407579                                      NaN                 NaN   \n",
       "2310788                                      NaN                 NaN   \n",
       "4650666                                      NaN                 NaN   \n",
       "7165602                                      NaN                 NaN   \n",
       "\n",
       "                                      race race_6_TEXT strategy - Topics  \n",
       "mTurkCode                                                                 \n",
       "2842236                              White         NaN               NaN  \n",
       "4563666                              White         NaN               NaN  \n",
       "6446494                              White         NaN               NaN  \n",
       "5261906                              White         NaN               NaN  \n",
       "5520318                              White         NaN               NaN  \n",
       "2262834                              White         NaN               NaN  \n",
       "8862928                              White         NaN               NaN  \n",
       "2120472                              White         NaN               NaN  \n",
       "5838413                              White         NaN               NaN  \n",
       "1694952                              White         NaN               NaN  \n",
       "3533894                              White         NaN               NaN  \n",
       "7189868                              White         NaN               NaN  \n",
       "5306294                              White         NaN               NaN  \n",
       "8623697                              White         NaN               NaN  \n",
       "8134166                              Asian         NaN               NaN  \n",
       "8596815                              White         NaN               NaN  \n",
       "6602150          Black or African American         NaN               NaN  \n",
       "3473940                              White         NaN               NaN  \n",
       "5269230                              White         NaN               NaN  \n",
       "5077941                              White         NaN               NaN  \n",
       "6168759                              White         NaN               NaN  \n",
       "6634401                              White         NaN               NaN  \n",
       "6026486                              White         NaN               NaN  \n",
       "1417422                              White         NaN               NaN  \n",
       "5672286                              Asian         NaN               NaN  \n",
       "5755149    White,Black or African American         NaN               NaN  \n",
       "7287504                              White         NaN               NaN  \n",
       "6675635                              White         NaN               NaN  \n",
       "7260435          Black or African American         NaN               NaN  \n",
       "5620933          Black or African American         NaN               NaN  \n",
       "...                                    ...         ...               ...  \n",
       "3010131                                NaN         NaN               NaN  \n",
       "8296099                                NaN         NaN               NaN  \n",
       "4972910                                NaN         NaN               NaN  \n",
       "1945826                                NaN         NaN               NaN  \n",
       "5037033                                NaN         NaN               NaN  \n",
       "7666564                                NaN         NaN               NaN  \n",
       "3626191                                NaN         NaN               NaN  \n",
       "5060255                                NaN         NaN               NaN  \n",
       "5009844                                NaN         NaN               NaN  \n",
       "7077643                                NaN         NaN               NaN  \n",
       "7545990                                NaN         NaN               NaN  \n",
       "8738901                                NaN         NaN               NaN  \n",
       "2217859                                NaN         NaN               NaN  \n",
       "8591661                                NaN         NaN               NaN  \n",
       "5828228                                NaN         NaN               NaN  \n",
       "4328917                                NaN         NaN               NaN  \n",
       "1089141                                NaN         NaN               NaN  \n",
       "4840647                                NaN         NaN               NaN  \n",
       "6682723                                NaN         NaN               NaN  \n",
       "3611286                                NaN         NaN               NaN  \n",
       "3332819                                NaN         NaN               NaN  \n",
       "4628194                                NaN         NaN               NaN  \n",
       "5718227                                NaN         NaN               NaN  \n",
       "5111805                                NaN         NaN               NaN  \n",
       "5895146                                NaN         NaN               NaN  \n",
       "8788125                                NaN         NaN               NaN  \n",
       "1407579                                NaN         NaN               NaN  \n",
       "2310788                                NaN         NaN               NaN  \n",
       "4650666                                NaN         NaN               NaN  \n",
       "7165602                                NaN         NaN               NaN  \n",
       "\n",
       "[2647 rows x 37 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#removing the duplicate title rows (they are added by default when exporting the data from qualtrics)\n",
    "df = df.drop(df.index[0:2])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p><strong>Exclude</strong> anyone who did not consent to be part of the experiment</p> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>StartDate</th>\n",
       "      <th>EndDate</th>\n",
       "      <th>Status</th>\n",
       "      <th>IPAddress</th>\n",
       "      <th>Progress</th>\n",
       "      <th>Duration (in seconds)</th>\n",
       "      <th>Finished</th>\n",
       "      <th>RecordedDate</th>\n",
       "      <th>ResponseId</th>\n",
       "      <th>RecipientLastName</th>\n",
       "      <th>...</th>\n",
       "      <th>strategy</th>\n",
       "      <th>experimentAbout</th>\n",
       "      <th>location</th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>education</th>\n",
       "      <th>Q32</th>\n",
       "      <th>race</th>\n",
       "      <th>race_6_TEXT</th>\n",
       "      <th>strategy - Topics</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mTurkCode</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2842236</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:12</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>51</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:12</td>\n",
       "      <td>R_vqUgiL0RrIcUZaN</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I want money</td>\n",
       "      <td>who cares</td>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4563666</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:12</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>47</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:12</td>\n",
       "      <td>R_a2A6STjMB7b7LnH</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I wanted to maximize my own earnings</td>\n",
       "      <td>I don't know</td>\n",
       "      <td>Virginia, USA</td>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6446494</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>112</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>R_3JwUGrCtLZRT0M0</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I want my max bonus.</td>\n",
       "      <td>To see how much people are willing to help oth...</td>\n",
       "      <td>CA, USA</td>\n",
       "      <td>21</td>\n",
       "      <td>Male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5261906</th>\n",
       "      <td>9/13/17 11:12</td>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>86</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>R_2Y6f8YlWkL9eYfm</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>i dunno</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USA, wa</td>\n",
       "      <td>26</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>under $5,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5520318</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>133</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>R_1mwRKmTWSfljrTR</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Give something back to the platform</td>\n",
       "      <td>Perception</td>\n",
       "      <td>USA Indiana</td>\n",
       "      <td>29</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2262834</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>138</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>R_6gRQdDFJJLce1JT</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I was sick of working for other people who did...</td>\n",
       "      <td>I have no idea.</td>\n",
       "      <td>Wisconsin, USA</td>\n",
       "      <td>35</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8862928</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>160</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>R_3EEI6vysVLsXxJS</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>for extra income</td>\n",
       "      <td>not sure</td>\n",
       "      <td>USA TN</td>\n",
       "      <td>49</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2120472</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>168</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>R_yCmJjtveHIVLkf7</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I didn't want to destroy anything</td>\n",
       "      <td>I have no idea</td>\n",
       "      <td>USA</td>\n",
       "      <td>38</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5838413</th>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>9/13/17 11:15</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>89</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:15</td>\n",
       "      <td>R_2SH0dL8FYg4ocr5</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I don't know the other person and I might need...</td>\n",
       "      <td>Generosity</td>\n",
       "      <td>MO, USA</td>\n",
       "      <td>26</td>\n",
       "      <td>female</td>\n",
       "      <td>High school graduate</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1694952</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:15</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>233</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:15</td>\n",
       "      <td>R_3EW2IwQIa8KqtRv</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I needed extra money since I am a student and ...</td>\n",
       "      <td>Not sure.</td>\n",
       "      <td>WA, USA</td>\n",
       "      <td>21</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>under $5,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3533894</th>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>9/13/17 11:16</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>82</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:16</td>\n",
       "      <td>R_ZI7cF6ge94QYSKR</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I was not sure how legitimate it was so i gave...</td>\n",
       "      <td>our generosity.</td>\n",
       "      <td>USA Wisconsin</td>\n",
       "      <td>30</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$80,001 - $100,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7189868</th>\n",
       "      <td>9/13/17 11:21</td>\n",
       "      <td>9/13/17 11:22</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>78</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:22</td>\n",
       "      <td>R_1kRzX8PSoNw2USA</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I wanted to maximize my earnings.</td>\n",
       "      <td>How people think about what they feel in certa...</td>\n",
       "      <td>USA, PA</td>\n",
       "      <td>36</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5306294</th>\n",
       "      <td>9/13/17 11:31</td>\n",
       "      <td>9/13/17 11:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>256</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:35</td>\n",
       "      <td>R_3lAohlIOjmfX3k5</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>From what I have seen in most studies no one g...</td>\n",
       "      <td>Morality</td>\n",
       "      <td>Vermont USA</td>\n",
       "      <td>44</td>\n",
       "      <td>Male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8623697</th>\n",
       "      <td>9/13/17 11:39</td>\n",
       "      <td>9/13/17 11:41</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>126</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:41</td>\n",
       "      <td>R_3hDRkTVTxO1olmd</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>There is no reason or incentive to give the bo...</td>\n",
       "      <td>Whether people are likely to give money away t...</td>\n",
       "      <td>OH, USA</td>\n",
       "      <td>30</td>\n",
       "      <td>male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8134166</th>\n",
       "      <td>9/13/17 15:01</td>\n",
       "      <td>9/13/17 15:03</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>113</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 15:03</td>\n",
       "      <td>R_s6V4HtdE4qD17t7</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I'm a greedy bastard, so my natural inclinatio...</td>\n",
       "      <td>I think it's studying human greed.</td>\n",
       "      <td>VA USA</td>\n",
       "      <td>25</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8596815</th>\n",
       "      <td>9/13/17 15:06</td>\n",
       "      <td>9/13/17 15:08</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>112</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 15:08</td>\n",
       "      <td>R_232EPK2fUxbl77l</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I need money</td>\n",
       "      <td>greed</td>\n",
       "      <td>USA PA</td>\n",
       "      <td>27</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6602150</th>\n",
       "      <td>9/13/17 16:12</td>\n",
       "      <td>9/13/17 16:15</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>152</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 16:15</td>\n",
       "      <td>R_1eKp3z27TvT7WQi</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I don't think there is another person</td>\n",
       "      <td>I'm not sure</td>\n",
       "      <td>NY, USA</td>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3473940</th>\n",
       "      <td>9/13/17 16:32</td>\n",
       "      <td>9/13/17 16:34</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>152</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 16:34</td>\n",
       "      <td>R_QoFTmmuZ9XpSU4V</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>My son got tired of giving me money so he did ...</td>\n",
       "      <td>traits of AMT workers</td>\n",
       "      <td>PA, USA</td>\n",
       "      <td>52</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5269230</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>78</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>R_5hvlsH77FVdJIYh</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I work for myself, and don't want to give away...</td>\n",
       "      <td>Charitable behavior.</td>\n",
       "      <td>USA - Pennsylvania</td>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5077941</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>71</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>R_3k7kOJwgYHGeln9</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I wanted to make more money.</td>\n",
       "      <td>generosity and whether people will donate more...</td>\n",
       "      <td>Portland Oregon USA</td>\n",
       "      <td>25</td>\n",
       "      <td>female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6168759</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>86</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>R_AdPRLInN2cVd3nb</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>It's fair and equal.</td>\n",
       "      <td>I'm not sure.  Kindness?</td>\n",
       "      <td>USA, Michigan</td>\n",
       "      <td>30</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6634401</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>R_3fVGV5ZkNuTrHHl</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I wanted to maximize my own bonus.</td>\n",
       "      <td>To see how giving other people are.</td>\n",
       "      <td>California, USA</td>\n",
       "      <td>26</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>Over $100,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6026486</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>91</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_3ndW3UKWnJSDZjH</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Mturk had the most consistent money.  It was i...</td>\n",
       "      <td>Use of mturk vs willingness to give.</td>\n",
       "      <td>Rochester New York, USA</td>\n",
       "      <td>40</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1417422</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>108</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_22Etas0RSwBu4LT</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I have only had luck at mturk</td>\n",
       "      <td>charitable giving responses</td>\n",
       "      <td>USA, Maine</td>\n",
       "      <td>31</td>\n",
       "      <td>Male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5672286</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>93</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_sXpd178WWp5Pufv</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Mostly beneficial to me</td>\n",
       "      <td>generosity of an individual</td>\n",
       "      <td>Massachusetts, USA</td>\n",
       "      <td>32</td>\n",
       "      <td>male</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$80,001 - $100,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5755149</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>131</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_WCf8iglKqxhslH3</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I'm greedy.</td>\n",
       "      <td>Attitudes on generosity.</td>\n",
       "      <td>Texas, USA</td>\n",
       "      <td>25</td>\n",
       "      <td>Female</td>\n",
       "      <td>High school graduate</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>White,Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7287504</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>147</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_bjXB1zGjFGhHbRn</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>because I have worked for mturk since 2015</td>\n",
       "      <td>how people react to different questions</td>\n",
       "      <td>Colorado, USA</td>\n",
       "      <td>33</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6675635</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>163</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_22yanStURNkDQVi</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I like the idea of fairness and karma. I hope ...</td>\n",
       "      <td>What peoples' reasoning for dedicating or not ...</td>\n",
       "      <td>Michigan, USA</td>\n",
       "      <td>31</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7260435</th>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>67</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_CdY8ShpwrwFtgM9</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>i wanted the bonus</td>\n",
       "      <td>unsure</td>\n",
       "      <td>USA GA</td>\n",
       "      <td>22</td>\n",
       "      <td>male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5620933</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:37</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>175</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:37</td>\n",
       "      <td>R_242XSYOv1tLo5FX</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Money is tight for me right now but I normally...</td>\n",
       "      <td>If people are willing to share</td>\n",
       "      <td>USA, Maryland</td>\n",
       "      <td>27</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
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       "      <th>4628194</th>\n",
       "      <td>9/18/17 7:56</td>\n",
       "      <td>9/18/17 7:59</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>48</td>\n",
       "      <td>188</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_25zJaKjkdgDKZty</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5718227</th>\n",
       "      <td>9/18/17 7:45</td>\n",
       "      <td>9/18/17 7:46</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>44</td>\n",
       "      <td>20</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_1g79UNYJPz6QwdC</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5111805</th>\n",
       "      <td>9/18/17 8:12</td>\n",
       "      <td>9/18/17 8:15</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>48</td>\n",
       "      <td>175</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_0V8oMQ0d6vA0M0N</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5895146</th>\n",
       "      <td>9/18/17 0:31</td>\n",
       "      <td>9/18/17 0:31</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>48</td>\n",
       "      <td>55</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_22y3QXmhxvkYD6s</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8788125</th>\n",
       "      <td>9/18/17 21:43</td>\n",
       "      <td>9/18/17 21:45</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>56</td>\n",
       "      <td>152</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_3EG1D3SZHHq0Y44</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1407579</th>\n",
       "      <td>9/18/17 21:06</td>\n",
       "      <td>9/18/17 21:08</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>56</td>\n",
       "      <td>98</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_3qU05gXnBr8vMV7</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2310788</th>\n",
       "      <td>9/18/17 12:34</td>\n",
       "      <td>9/18/17 12:34</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>48</td>\n",
       "      <td>42</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_3iBWq356sut7DSm</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4650666</th>\n",
       "      <td>9/18/17 12:36</td>\n",
       "      <td>9/18/17 12:38</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>56</td>\n",
       "      <td>117</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_21z9OVauxE9qFF3</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7165602</th>\n",
       "      <td>9/18/17 12:39</td>\n",
       "      <td>9/18/17 12:40</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>56</td>\n",
       "      <td>83</td>\n",
       "      <td>FALSE</td>\n",
       "      <td>9/24/17 21:22</td>\n",
       "      <td>R_3ezr0xwCUGGllMI</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2644 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               StartDate        EndDate      Status IPAddress Progress  \\\n",
       "mTurkCode                                                                \n",
       "2842236    9/13/17 11:11  9/13/17 11:12  IP Address   *******      100   \n",
       "4563666    9/13/17 11:11  9/13/17 11:12  IP Address   *******      100   \n",
       "6446494    9/13/17 11:11  9/13/17 11:13  IP Address   *******      100   \n",
       "5261906    9/13/17 11:12  9/13/17 11:13  IP Address   *******      100   \n",
       "5520318    9/13/17 11:11  9/13/17 11:13  IP Address   *******      100   \n",
       "2262834    9/13/17 11:11  9/13/17 11:14  IP Address   *******      100   \n",
       "8862928    9/13/17 11:11  9/13/17 11:14  IP Address   *******      100   \n",
       "2120472    9/13/17 11:11  9/13/17 11:14  IP Address   *******      100   \n",
       "5838413    9/13/17 11:13  9/13/17 11:15  IP Address   *******      100   \n",
       "1694952    9/13/17 11:11  9/13/17 11:15  IP Address   *******      100   \n",
       "3533894    9/13/17 11:14  9/13/17 11:16  IP Address   *******      100   \n",
       "7189868    9/13/17 11:21  9/13/17 11:22  IP Address   *******      100   \n",
       "5306294    9/13/17 11:31  9/13/17 11:35  IP Address   *******      100   \n",
       "8623697    9/13/17 11:39  9/13/17 11:41  IP Address   *******      100   \n",
       "8134166    9/13/17 15:01  9/13/17 15:03  IP Address   *******      100   \n",
       "8596815    9/13/17 15:06  9/13/17 15:08  IP Address   *******      100   \n",
       "6602150    9/13/17 16:12  9/13/17 16:15  IP Address   *******      100   \n",
       "3473940    9/13/17 16:32  9/13/17 16:34  IP Address   *******      100   \n",
       "5269230    9/13/17 20:34  9/13/17 20:35  IP Address   *******      100   \n",
       "5077941    9/13/17 20:34  9/13/17 20:35  IP Address   *******      100   \n",
       "6168759    9/13/17 20:34  9/13/17 20:35  IP Address   *******      100   \n",
       "6634401    9/13/17 20:34  9/13/17 20:35  IP Address   *******      100   \n",
       "6026486    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "1417422    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "5672286    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "5755149    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "7287504    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "6675635    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "7260435    9/13/17 20:35  9/13/17 20:36  IP Address   *******      100   \n",
       "5620933    9/13/17 20:34  9/13/17 20:37  IP Address   *******      100   \n",
       "...                  ...            ...         ...       ...      ...   \n",
       "3010131    9/17/17 22:04  9/17/17 22:17  IP Address   *******       56   \n",
       "8296099    9/17/17 22:20  9/17/17 22:22  IP Address   *******       56   \n",
       "4972910     9/18/17 0:27   9/18/17 0:28  IP Address   *******       48   \n",
       "1945826     9/18/17 1:18   9/18/17 1:26  IP Address   *******       56   \n",
       "5037033     9/18/17 2:06   9/18/17 2:07  IP Address   *******       48   \n",
       "7666564     9/18/17 7:59   9/18/17 8:01  IP Address   *******       48   \n",
       "3626191     9/18/17 8:03   9/18/17 8:04  IP Address   *******       48   \n",
       "5060255     9/18/17 9:51   9/18/17 9:58  IP Address   *******       48   \n",
       "5009844     9/18/17 9:40   9/18/17 9:43  IP Address   *******       56   \n",
       "7077643    9/18/17 11:04  9/18/17 11:06  IP Address   *******       56   \n",
       "7545990    9/18/17 21:26  9/18/17 21:27  IP Address   *******       44   \n",
       "8738901    9/18/17 16:01  9/18/17 16:02  IP Address   *******       56   \n",
       "2217859     9/18/17 7:45   9/18/17 7:46  IP Address   *******       48   \n",
       "8591661     9/18/17 8:39   9/18/17 8:39  IP Address   *******       44   \n",
       "5828228     9/18/17 8:07   9/18/17 8:20  IP Address   *******       56   \n",
       "4328917     9/18/17 8:45   9/18/17 8:51  IP Address   *******       56   \n",
       "1089141    9/18/17 10:40  9/18/17 10:42  IP Address   *******       48   \n",
       "4840647    9/18/17 12:23  9/18/17 12:25  IP Address   *******       48   \n",
       "6682723    9/18/17 12:27  9/18/17 12:29  IP Address   *******       56   \n",
       "3611286    9/18/17 21:07  9/18/17 21:08  IP Address   *******       48   \n",
       "3332819    9/21/17 21:24   9/22/17 8:18  IP Address   *******       48   \n",
       "4628194     9/18/17 7:56   9/18/17 7:59  IP Address   *******       48   \n",
       "5718227     9/18/17 7:45   9/18/17 7:46  IP Address   *******       44   \n",
       "5111805     9/18/17 8:12   9/18/17 8:15  IP Address   *******       48   \n",
       "5895146     9/18/17 0:31   9/18/17 0:31  IP Address   *******       48   \n",
       "8788125    9/18/17 21:43  9/18/17 21:45  IP Address   *******       56   \n",
       "1407579    9/18/17 21:06  9/18/17 21:08  IP Address   *******       56   \n",
       "2310788    9/18/17 12:34  9/18/17 12:34  IP Address   *******       48   \n",
       "4650666    9/18/17 12:36  9/18/17 12:38  IP Address   *******       56   \n",
       "7165602    9/18/17 12:39  9/18/17 12:40  IP Address   *******       56   \n",
       "\n",
       "          Duration (in seconds) Finished   RecordedDate         ResponseId  \\\n",
       "mTurkCode                                                                    \n",
       "2842236                      51     TRUE  9/13/17 11:12  R_vqUgiL0RrIcUZaN   \n",
       "4563666                      47     TRUE  9/13/17 11:12  R_a2A6STjMB7b7LnH   \n",
       "6446494                     112     TRUE  9/13/17 11:13  R_3JwUGrCtLZRT0M0   \n",
       "5261906                      86     TRUE  9/13/17 11:13  R_2Y6f8YlWkL9eYfm   \n",
       "5520318                     133     TRUE  9/13/17 11:13  R_1mwRKmTWSfljrTR   \n",
       "2262834                     138     TRUE  9/13/17 11:14  R_6gRQdDFJJLce1JT   \n",
       "8862928                     160     TRUE  9/13/17 11:14  R_3EEI6vysVLsXxJS   \n",
       "2120472                     168     TRUE  9/13/17 11:14  R_yCmJjtveHIVLkf7   \n",
       "5838413                      89     TRUE  9/13/17 11:15  R_2SH0dL8FYg4ocr5   \n",
       "1694952                     233     TRUE  9/13/17 11:15  R_3EW2IwQIa8KqtRv   \n",
       "3533894                      82     TRUE  9/13/17 11:16  R_ZI7cF6ge94QYSKR   \n",
       "7189868                      78     TRUE  9/13/17 11:22  R_1kRzX8PSoNw2USA   \n",
       "5306294                     256     TRUE  9/13/17 11:35  R_3lAohlIOjmfX3k5   \n",
       "8623697                     126     TRUE  9/13/17 11:41  R_3hDRkTVTxO1olmd   \n",
       "8134166                     113     TRUE  9/13/17 15:03  R_s6V4HtdE4qD17t7   \n",
       "8596815                     112     TRUE  9/13/17 15:08  R_232EPK2fUxbl77l   \n",
       "6602150                     152     TRUE  9/13/17 16:15  R_1eKp3z27TvT7WQi   \n",
       "3473940                     152     TRUE  9/13/17 16:34  R_QoFTmmuZ9XpSU4V   \n",
       "5269230                      78     TRUE  9/13/17 20:35  R_5hvlsH77FVdJIYh   \n",
       "5077941                      71     TRUE  9/13/17 20:35  R_3k7kOJwgYHGeln9   \n",
       "6168759                      86     TRUE  9/13/17 20:35  R_AdPRLInN2cVd3nb   \n",
       "6634401                      75     TRUE  9/13/17 20:35  R_3fVGV5ZkNuTrHHl   \n",
       "6026486                      91     TRUE  9/13/17 20:36  R_3ndW3UKWnJSDZjH   \n",
       "1417422                     108     TRUE  9/13/17 20:36  R_22Etas0RSwBu4LT   \n",
       "5672286                      93     TRUE  9/13/17 20:36  R_sXpd178WWp5Pufv   \n",
       "5755149                     131     TRUE  9/13/17 20:36  R_WCf8iglKqxhslH3   \n",
       "7287504                     147     TRUE  9/13/17 20:36  R_bjXB1zGjFGhHbRn   \n",
       "6675635                     163     TRUE  9/13/17 20:36  R_22yanStURNkDQVi   \n",
       "7260435                      67     TRUE  9/13/17 20:36  R_CdY8ShpwrwFtgM9   \n",
       "5620933                     175     TRUE  9/13/17 20:37  R_242XSYOv1tLo5FX   \n",
       "...                         ...      ...            ...                ...   \n",
       "3010131                     754    FALSE  9/24/17 21:22  R_2947AC86K75R3j2   \n",
       "8296099                     151    FALSE  9/24/17 21:22  R_22s2xF09Vvs197n   \n",
       "4972910                      80    FALSE  9/24/17 21:22  R_1BXdXKFEhPPgfYN   \n",
       "1945826                     456    FALSE  9/24/17 21:22  R_3MECPgZSFbAKkSu   \n",
       "5037033                      50    FALSE  9/24/17 21:22  R_33Duo2nSnRAx7WK   \n",
       "7666564                     119    FALSE  9/24/17 21:22  R_3fVpizHuyDIdLoG   \n",
       "3626191                      72    FALSE  9/24/17 21:22  R_1LI3Ldd987I0Z5I   \n",
       "5060255                     427    FALSE  9/24/17 21:22  R_2dQLQ9sRXGxqfTy   \n",
       "5009844                     204    FALSE  9/24/17 21:22  R_1Q61p15frP3k8V6   \n",
       "7077643                      89    FALSE  9/24/17 21:22  R_2tAwrH0I6fYwlPs   \n",
       "7545990                      20    FALSE  9/24/17 21:22  R_eeQIUTZmfaInKp3   \n",
       "8738901                      94    FALSE  9/24/17 21:22  R_24iszkMRqf1L6ri   \n",
       "2217859                      53    FALSE  9/24/17 21:22  R_3kM52bPemSgNj7S   \n",
       "8591661                      29    FALSE  9/24/17 21:22  R_2AF0gEcEsNe2ClT   \n",
       "5828228                     761    FALSE  9/24/17 21:22  R_BxFldZ7wDPsgJ45   \n",
       "4328917                     354    FALSE  9/24/17 21:22  R_3FOFg7mX859fnFX   \n",
       "1089141                     158    FALSE  9/24/17 21:22  R_voF5rzmFWHGI6GJ   \n",
       "4840647                     124    FALSE  9/24/17 21:22  R_1GObuCyWlIy6Zvl   \n",
       "6682723                     174    FALSE  9/24/17 21:22  R_2xQ1MwDPb9ymnoI   \n",
       "3611286                      34    FALSE  9/24/17 21:22  R_sBDh2yPwc6qnvUt   \n",
       "3332819                   39215    FALSE  9/24/17 21:22  R_1FP2WxQNP8jrEEp   \n",
       "4628194                     188    FALSE  9/24/17 21:22  R_25zJaKjkdgDKZty   \n",
       "5718227                      20    FALSE  9/24/17 21:22  R_1g79UNYJPz6QwdC   \n",
       "5111805                     175    FALSE  9/24/17 21:22  R_0V8oMQ0d6vA0M0N   \n",
       "5895146                      55    FALSE  9/24/17 21:22  R_22y3QXmhxvkYD6s   \n",
       "8788125                     152    FALSE  9/24/17 21:22  R_3EG1D3SZHHq0Y44   \n",
       "1407579                      98    FALSE  9/24/17 21:22  R_3qU05gXnBr8vMV7   \n",
       "2310788                      42    FALSE  9/24/17 21:22  R_3iBWq356sut7DSm   \n",
       "4650666                     117    FALSE  9/24/17 21:22  R_21z9OVauxE9qFF3   \n",
       "7165602                      83    FALSE  9/24/17 21:22  R_3ezr0xwCUGGllMI   \n",
       "\n",
       "          RecipientLastName        ...         \\\n",
       "mTurkCode                          ...          \n",
       "2842236             *******        ...          \n",
       "4563666             *******        ...          \n",
       "6446494             *******        ...          \n",
       "5261906             *******        ...          \n",
       "5520318             *******        ...          \n",
       "2262834             *******        ...          \n",
       "8862928             *******        ...          \n",
       "2120472             *******        ...          \n",
       "5838413             *******        ...          \n",
       "1694952             *******        ...          \n",
       "3533894             *******        ...          \n",
       "7189868             *******        ...          \n",
       "5306294             *******        ...          \n",
       "8623697             *******        ...          \n",
       "8134166             *******        ...          \n",
       "8596815             *******        ...          \n",
       "6602150             *******        ...          \n",
       "3473940             *******        ...          \n",
       "5269230             *******        ...          \n",
       "5077941             *******        ...          \n",
       "6168759             *******        ...          \n",
       "6634401             *******        ...          \n",
       "6026486             *******        ...          \n",
       "1417422             *******        ...          \n",
       "5672286             *******        ...          \n",
       "5755149             *******        ...          \n",
       "7287504             *******        ...          \n",
       "6675635             *******        ...          \n",
       "7260435             *******        ...          \n",
       "5620933             *******        ...          \n",
       "...                     ...        ...          \n",
       "3010131             *******        ...          \n",
       "8296099             *******        ...          \n",
       "4972910             *******        ...          \n",
       "1945826             *******        ...          \n",
       "5037033             *******        ...          \n",
       "7666564             *******        ...          \n",
       "3626191             *******        ...          \n",
       "5060255             *******        ...          \n",
       "5009844             *******        ...          \n",
       "7077643             *******        ...          \n",
       "7545990             *******        ...          \n",
       "8738901             *******        ...          \n",
       "2217859             *******        ...          \n",
       "8591661             *******        ...          \n",
       "5828228             *******        ...          \n",
       "4328917             *******        ...          \n",
       "1089141             *******        ...          \n",
       "4840647             *******        ...          \n",
       "6682723             *******        ...          \n",
       "3611286             *******        ...          \n",
       "3332819             *******        ...          \n",
       "4628194             *******        ...          \n",
       "5718227             *******        ...          \n",
       "5111805             *******        ...          \n",
       "5895146             *******        ...          \n",
       "8788125             *******        ...          \n",
       "1407579             *******        ...          \n",
       "2310788             *******        ...          \n",
       "4650666             *******        ...          \n",
       "7165602             *******        ...          \n",
       "\n",
       "                                                    strategy  \\\n",
       "mTurkCode                                                      \n",
       "2842236                                         I want money   \n",
       "4563666                 I wanted to maximize my own earnings   \n",
       "6446494                                 I want my max bonus.   \n",
       "5261906                                              i dunno   \n",
       "5520318                 Give something back to the platform    \n",
       "2262834    I was sick of working for other people who did...   \n",
       "8862928                                     for extra income   \n",
       "2120472                    I didn't want to destroy anything   \n",
       "5838413    I don't know the other person and I might need...   \n",
       "1694952    I needed extra money since I am a student and ...   \n",
       "3533894    I was not sure how legitimate it was so i gave...   \n",
       "7189868                    I wanted to maximize my earnings.   \n",
       "5306294    From what I have seen in most studies no one g...   \n",
       "8623697    There is no reason or incentive to give the bo...   \n",
       "8134166    I'm a greedy bastard, so my natural inclinatio...   \n",
       "8596815                                         I need money   \n",
       "6602150                I don't think there is another person   \n",
       "3473940    My son got tired of giving me money so he did ...   \n",
       "5269230    I work for myself, and don't want to give away...   \n",
       "5077941                         I wanted to make more money.   \n",
       "6168759                                 It's fair and equal.   \n",
       "6634401                   I wanted to maximize my own bonus.   \n",
       "6026486    Mturk had the most consistent money.  It was i...   \n",
       "1417422                        I have only had luck at mturk   \n",
       "5672286                              Mostly beneficial to me   \n",
       "5755149                                          I'm greedy.   \n",
       "7287504           because I have worked for mturk since 2015   \n",
       "6675635    I like the idea of fairness and karma. I hope ...   \n",
       "7260435                                   i wanted the bonus   \n",
       "5620933    Money is tight for me right now but I normally...   \n",
       "...                                                      ...   \n",
       "3010131                                                  NaN   \n",
       "8296099                                                  NaN   \n",
       "4972910                                                  NaN   \n",
       "1945826                                                  NaN   \n",
       "5037033                                                  NaN   \n",
       "7666564                                                  NaN   \n",
       "3626191                                                  NaN   \n",
       "5060255                                                  NaN   \n",
       "5009844                                                  NaN   \n",
       "7077643                                                  NaN   \n",
       "7545990                                                  NaN   \n",
       "8738901                                                  NaN   \n",
       "2217859                                                  NaN   \n",
       "8591661                                                  NaN   \n",
       "5828228                                                  NaN   \n",
       "4328917                                                  NaN   \n",
       "1089141                                                  NaN   \n",
       "4840647                                                  NaN   \n",
       "6682723                                                  NaN   \n",
       "3611286                                                  NaN   \n",
       "3332819                                                  NaN   \n",
       "4628194                                                  NaN   \n",
       "5718227                                                  NaN   \n",
       "5111805                                                  NaN   \n",
       "5895146                                                  NaN   \n",
       "8788125                                                  NaN   \n",
       "1407579                                                  NaN   \n",
       "2310788                                                  NaN   \n",
       "4650666                                                  NaN   \n",
       "7165602                                                  NaN   \n",
       "\n",
       "                                             experimentAbout  \\\n",
       "mTurkCode                                                      \n",
       "2842236                                            who cares   \n",
       "4563666                                         I don't know   \n",
       "6446494    To see how much people are willing to help oth...   \n",
       "5261906                                                  NaN   \n",
       "5520318                                          Perception    \n",
       "2262834                                     I have no idea.    \n",
       "8862928                                             not sure   \n",
       "2120472                                       I have no idea   \n",
       "5838413                                          Generosity    \n",
       "1694952                                           Not sure.    \n",
       "3533894                                      our generosity.   \n",
       "7189868    How people think about what they feel in certa...   \n",
       "5306294                                            Morality    \n",
       "8623697    Whether people are likely to give money away t...   \n",
       "8134166                  I think it's studying human greed.    \n",
       "8596815                                                greed   \n",
       "6602150                                         I'm not sure   \n",
       "3473940                                traits of AMT workers   \n",
       "5269230                                 Charitable behavior.   \n",
       "5077941    generosity and whether people will donate more...   \n",
       "6168759                             I'm not sure.  Kindness?   \n",
       "6634401                  To see how giving other people are.   \n",
       "6026486               Use of mturk vs willingness to give.     \n",
       "1417422                          charitable giving responses   \n",
       "5672286                          generosity of an individual   \n",
       "5755149                             Attitudes on generosity.   \n",
       "7287504              how people react to different questions   \n",
       "6675635    What peoples' reasoning for dedicating or not ...   \n",
       "7260435                                               unsure   \n",
       "5620933                       If people are willing to share   \n",
       "...                                                      ...   \n",
       "3010131                                                  NaN   \n",
       "8296099                                                  NaN   \n",
       "4972910                                                  NaN   \n",
       "1945826                                                  NaN   \n",
       "5037033                                                  NaN   \n",
       "7666564                                                  NaN   \n",
       "3626191                                                  NaN   \n",
       "5060255                                                  NaN   \n",
       "5009844                                                  NaN   \n",
       "7077643                                                  NaN   \n",
       "7545990                                                  NaN   \n",
       "8738901                                                  NaN   \n",
       "2217859                                                  NaN   \n",
       "8591661                                                  NaN   \n",
       "5828228                                                  NaN   \n",
       "4328917                                                  NaN   \n",
       "1089141                                                  NaN   \n",
       "4840647                                                  NaN   \n",
       "6682723                                                  NaN   \n",
       "3611286                                                  NaN   \n",
       "3332819                                                  NaN   \n",
       "4628194                                                  NaN   \n",
       "5718227                                                  NaN   \n",
       "5111805                                                  NaN   \n",
       "5895146                                                  NaN   \n",
       "8788125                                                  NaN   \n",
       "1407579                                                  NaN   \n",
       "2310788                                                  NaN   \n",
       "4650666                                                  NaN   \n",
       "7165602                                                  NaN   \n",
       "\n",
       "                          location  age     sex  \\\n",
       "mTurkCode                                         \n",
       "2842236                        USA   25    male   \n",
       "4563666              Virginia, USA   27    Male   \n",
       "6446494                    CA, USA   21    Male   \n",
       "5261906                    USA, wa   26  female   \n",
       "5520318               USA Indiana    29    Male   \n",
       "2262834             Wisconsin, USA   35    Male   \n",
       "8862928                     USA TN   49  Female   \n",
       "2120472                        USA   38  female   \n",
       "5838413                    MO, USA   26  female   \n",
       "1694952                    WA, USA   21  Female   \n",
       "3533894              USA Wisconsin   30    male   \n",
       "7189868                    USA, PA   36    male   \n",
       "5306294                Vermont USA   44   Male    \n",
       "8623697                    OH, USA   30    male   \n",
       "8134166                     VA USA   25    Male   \n",
       "8596815                     USA PA   27    male   \n",
       "6602150                    NY, USA   27    Male   \n",
       "3473940                    PA, USA   52  female   \n",
       "5269230         USA - Pennsylvania   27    Male   \n",
       "5077941        Portland Oregon USA   25  female   \n",
       "6168759              USA, Michigan   30  Female   \n",
       "6634401            California, USA   26    Male   \n",
       "6026486    Rochester New York, USA   40    Male   \n",
       "1417422                 USA, Maine   31    Male   \n",
       "5672286         Massachusetts, USA   32    male   \n",
       "5755149                 Texas, USA   25  Female   \n",
       "7287504              Colorado, USA   33  Female   \n",
       "6675635              Michigan, USA   31  Female   \n",
       "7260435                     USA GA   22    male   \n",
       "5620933              USA, Maryland   27  female   \n",
       "...                            ...  ...     ...   \n",
       "3010131                        NaN  NaN     NaN   \n",
       "8296099                        NaN  NaN     NaN   \n",
       "4972910                        NaN  NaN     NaN   \n",
       "1945826                        NaN  NaN     NaN   \n",
       "5037033                        NaN  NaN     NaN   \n",
       "7666564                        NaN  NaN     NaN   \n",
       "3626191                        NaN  NaN     NaN   \n",
       "5060255                        NaN  NaN     NaN   \n",
       "5009844                        NaN  NaN     NaN   \n",
       "7077643                        NaN  NaN     NaN   \n",
       "7545990                        NaN  NaN     NaN   \n",
       "8738901                        NaN  NaN     NaN   \n",
       "2217859                        NaN  NaN     NaN   \n",
       "8591661                        NaN  NaN     NaN   \n",
       "5828228                        NaN  NaN     NaN   \n",
       "4328917                        NaN  NaN     NaN   \n",
       "1089141                        NaN  NaN     NaN   \n",
       "4840647                        NaN  NaN     NaN   \n",
       "6682723                        NaN  NaN     NaN   \n",
       "3611286                        NaN  NaN     NaN   \n",
       "3332819                        NaN  NaN     NaN   \n",
       "4628194                        NaN  NaN     NaN   \n",
       "5718227                        NaN  NaN     NaN   \n",
       "5111805                        NaN  NaN     NaN   \n",
       "5895146                        NaN  NaN     NaN   \n",
       "8788125                        NaN  NaN     NaN   \n",
       "1407579                        NaN  NaN     NaN   \n",
       "2310788                        NaN  NaN     NaN   \n",
       "4650666                        NaN  NaN     NaN   \n",
       "7165602                        NaN  NaN     NaN   \n",
       "\n",
       "                                       education                 Q32  \\\n",
       "mTurkCode                                                              \n",
       "2842236    Bachelor's degree in college (4-year)   $25,001 - $35,000   \n",
       "4563666               Some college but no degree   $15,001 - $25,000   \n",
       "6446494     Associate degree in college (2-year)   $15,001 - $25,000   \n",
       "5261906               Some college but no degree        under $5,000   \n",
       "5520318    Bachelor's degree in college (4-year)   $65,001 - $80,000   \n",
       "2262834    Bachelor's degree in college (4-year)   $25,001 - $35,000   \n",
       "8862928               Some college but no degree  $50,001 -  $65,000   \n",
       "2120472               Some college but no degree   $65,001 - $80,000   \n",
       "5838413                     High school graduate   $25,001 - $35,000   \n",
       "1694952               Some college but no degree        under $5,000   \n",
       "3533894    Bachelor's degree in college (4-year)  $80,001 - $100,000   \n",
       "7189868    Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "5306294     Associate degree in college (2-year)   $25,001 - $35,000   \n",
       "8623697     Associate degree in college (2-year)   $15,001 - $25,000   \n",
       "8134166    Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "8596815    Bachelor's degree in college (4-year)    $5,000 - $10,000   \n",
       "6602150               Some college but no degree  $50,001 -  $65,000   \n",
       "3473940               Some college but no degree   $10,001 - $15,000   \n",
       "5269230                          Master's degree   $25,001 - $35,000   \n",
       "5077941    Bachelor's degree in college (4-year)   $10,001 - $15,000   \n",
       "6168759               Some college but no degree   $15,001 - $25,000   \n",
       "6634401    Bachelor's degree in college (4-year)       Over $100,000   \n",
       "6026486    Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "1417422     Associate degree in college (2-year)   $65,001 - $80,000   \n",
       "5672286                          Master's degree  $80,001 - $100,000   \n",
       "5755149                     High school graduate   $10,001 - $15,000   \n",
       "7287504               Some college but no degree  $50,001 -  $65,000   \n",
       "6675635               Some college but no degree    $5,000 - $10,000   \n",
       "7260435               Some college but no degree   $25,001 - $35,000   \n",
       "5620933               Some college but no degree    $5,000 - $10,000   \n",
       "...                                          ...                 ...   \n",
       "3010131                                      NaN                 NaN   \n",
       "8296099                                      NaN                 NaN   \n",
       "4972910                                      NaN                 NaN   \n",
       "1945826                                      NaN                 NaN   \n",
       "5037033                                      NaN                 NaN   \n",
       "7666564                                      NaN                 NaN   \n",
       "3626191                                      NaN                 NaN   \n",
       "5060255                                      NaN                 NaN   \n",
       "5009844                                      NaN                 NaN   \n",
       "7077643                                      NaN                 NaN   \n",
       "7545990                                      NaN                 NaN   \n",
       "8738901                                      NaN                 NaN   \n",
       "2217859                                      NaN                 NaN   \n",
       "8591661                                      NaN                 NaN   \n",
       "5828228                                      NaN                 NaN   \n",
       "4328917                                      NaN                 NaN   \n",
       "1089141                                      NaN                 NaN   \n",
       "4840647                                      NaN                 NaN   \n",
       "6682723                                      NaN                 NaN   \n",
       "3611286                                      NaN                 NaN   \n",
       "3332819                                      NaN                 NaN   \n",
       "4628194                                      NaN                 NaN   \n",
       "5718227                                      NaN                 NaN   \n",
       "5111805                                      NaN                 NaN   \n",
       "5895146                                      NaN                 NaN   \n",
       "8788125                                      NaN                 NaN   \n",
       "1407579                                      NaN                 NaN   \n",
       "2310788                                      NaN                 NaN   \n",
       "4650666                                      NaN                 NaN   \n",
       "7165602                                      NaN                 NaN   \n",
       "\n",
       "                                      race race_6_TEXT strategy - Topics  \n",
       "mTurkCode                                                                 \n",
       "2842236                              White         NaN               NaN  \n",
       "4563666                              White         NaN               NaN  \n",
       "6446494                              White         NaN               NaN  \n",
       "5261906                              White         NaN               NaN  \n",
       "5520318                              White         NaN               NaN  \n",
       "2262834                              White         NaN               NaN  \n",
       "8862928                              White         NaN               NaN  \n",
       "2120472                              White         NaN               NaN  \n",
       "5838413                              White         NaN               NaN  \n",
       "1694952                              White         NaN               NaN  \n",
       "3533894                              White         NaN               NaN  \n",
       "7189868                              White         NaN               NaN  \n",
       "5306294                              White         NaN               NaN  \n",
       "8623697                              White         NaN               NaN  \n",
       "8134166                              Asian         NaN               NaN  \n",
       "8596815                              White         NaN               NaN  \n",
       "6602150          Black or African American         NaN               NaN  \n",
       "3473940                              White         NaN               NaN  \n",
       "5269230                              White         NaN               NaN  \n",
       "5077941                              White         NaN               NaN  \n",
       "6168759                              White         NaN               NaN  \n",
       "6634401                              White         NaN               NaN  \n",
       "6026486                              White         NaN               NaN  \n",
       "1417422                              White         NaN               NaN  \n",
       "5672286                              Asian         NaN               NaN  \n",
       "5755149    White,Black or African American         NaN               NaN  \n",
       "7287504                              White         NaN               NaN  \n",
       "6675635                              White         NaN               NaN  \n",
       "7260435          Black or African American         NaN               NaN  \n",
       "5620933          Black or African American         NaN               NaN  \n",
       "...                                    ...         ...               ...  \n",
       "3010131                                NaN         NaN               NaN  \n",
       "8296099                                NaN         NaN               NaN  \n",
       "4972910                                NaN         NaN               NaN  \n",
       "1945826                                NaN         NaN               NaN  \n",
       "5037033                                NaN         NaN               NaN  \n",
       "7666564                                NaN         NaN               NaN  \n",
       "3626191                                NaN         NaN               NaN  \n",
       "5060255                                NaN         NaN               NaN  \n",
       "5009844                                NaN         NaN               NaN  \n",
       "7077643                                NaN         NaN               NaN  \n",
       "7545990                                NaN         NaN               NaN  \n",
       "8738901                                NaN         NaN               NaN  \n",
       "2217859                                NaN         NaN               NaN  \n",
       "8591661                                NaN         NaN               NaN  \n",
       "5828228                                NaN         NaN               NaN  \n",
       "4328917                                NaN         NaN               NaN  \n",
       "1089141                                NaN         NaN               NaN  \n",
       "4840647                                NaN         NaN               NaN  \n",
       "6682723                                NaN         NaN               NaN  \n",
       "3611286                                NaN         NaN               NaN  \n",
       "3332819                                NaN         NaN               NaN  \n",
       "4628194                                NaN         NaN               NaN  \n",
       "5718227                                NaN         NaN               NaN  \n",
       "5111805                                NaN         NaN               NaN  \n",
       "5895146                                NaN         NaN               NaN  \n",
       "8788125                                NaN         NaN               NaN  \n",
       "1407579                                NaN         NaN               NaN  \n",
       "2310788                                NaN         NaN               NaN  \n",
       "4650666                                NaN         NaN               NaN  \n",
       "7165602                                NaN         NaN               NaN  \n",
       "\n",
       "[2644 rows x 37 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[df.consent_q==\"AGREE\"]\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p>Only have people who finished the survey (i.e., did not drop)</p>\n",
    "<p> Note the survey was spammed after we finished the experiment on the 18th of Sept 2017 .. However, the malicious activity that submitted around 100 survys none of them were compeleted, so this will clean it up</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>StartDate</th>\n",
       "      <th>EndDate</th>\n",
       "      <th>Status</th>\n",
       "      <th>IPAddress</th>\n",
       "      <th>Progress</th>\n",
       "      <th>Duration (in seconds)</th>\n",
       "      <th>Finished</th>\n",
       "      <th>RecordedDate</th>\n",
       "      <th>ResponseId</th>\n",
       "      <th>RecipientLastName</th>\n",
       "      <th>...</th>\n",
       "      <th>strategy</th>\n",
       "      <th>experimentAbout</th>\n",
       "      <th>location</th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>education</th>\n",
       "      <th>Q32</th>\n",
       "      <th>race</th>\n",
       "      <th>race_6_TEXT</th>\n",
       "      <th>strategy - Topics</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mTurkCode</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2842236</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:12</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>51</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:12</td>\n",
       "      <td>R_vqUgiL0RrIcUZaN</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I want money</td>\n",
       "      <td>who cares</td>\n",
       "      <td>USA</td>\n",
       "      <td>25</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4563666</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:12</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>47</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:12</td>\n",
       "      <td>R_a2A6STjMB7b7LnH</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I wanted to maximize my own earnings</td>\n",
       "      <td>I don't know</td>\n",
       "      <td>Virginia, USA</td>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6446494</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>112</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>R_3JwUGrCtLZRT0M0</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I want my max bonus.</td>\n",
       "      <td>To see how much people are willing to help oth...</td>\n",
       "      <td>CA, USA</td>\n",
       "      <td>21</td>\n",
       "      <td>Male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5261906</th>\n",
       "      <td>9/13/17 11:12</td>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>86</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>R_2Y6f8YlWkL9eYfm</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>i dunno</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USA, wa</td>\n",
       "      <td>26</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>under $5,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5520318</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>133</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>R_1mwRKmTWSfljrTR</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Give something back to the platform</td>\n",
       "      <td>Perception</td>\n",
       "      <td>USA Indiana</td>\n",
       "      <td>29</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2262834</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>138</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>R_6gRQdDFJJLce1JT</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I was sick of working for other people who did...</td>\n",
       "      <td>I have no idea.</td>\n",
       "      <td>Wisconsin, USA</td>\n",
       "      <td>35</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8862928</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>160</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>R_3EEI6vysVLsXxJS</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>for extra income</td>\n",
       "      <td>not sure</td>\n",
       "      <td>USA TN</td>\n",
       "      <td>49</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2120472</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>168</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>R_yCmJjtveHIVLkf7</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I didn't want to destroy anything</td>\n",
       "      <td>I have no idea</td>\n",
       "      <td>USA</td>\n",
       "      <td>38</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5838413</th>\n",
       "      <td>9/13/17 11:13</td>\n",
       "      <td>9/13/17 11:15</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>89</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:15</td>\n",
       "      <td>R_2SH0dL8FYg4ocr5</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I don't know the other person and I might need...</td>\n",
       "      <td>Generosity</td>\n",
       "      <td>MO, USA</td>\n",
       "      <td>26</td>\n",
       "      <td>female</td>\n",
       "      <td>High school graduate</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1694952</th>\n",
       "      <td>9/13/17 11:11</td>\n",
       "      <td>9/13/17 11:15</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>233</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:15</td>\n",
       "      <td>R_3EW2IwQIa8KqtRv</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I needed extra money since I am a student and ...</td>\n",
       "      <td>Not sure.</td>\n",
       "      <td>WA, USA</td>\n",
       "      <td>21</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>under $5,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3533894</th>\n",
       "      <td>9/13/17 11:14</td>\n",
       "      <td>9/13/17 11:16</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>82</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:16</td>\n",
       "      <td>R_ZI7cF6ge94QYSKR</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I was not sure how legitimate it was so i gave...</td>\n",
       "      <td>our generosity.</td>\n",
       "      <td>USA Wisconsin</td>\n",
       "      <td>30</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$80,001 - $100,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7189868</th>\n",
       "      <td>9/13/17 11:21</td>\n",
       "      <td>9/13/17 11:22</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>78</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:22</td>\n",
       "      <td>R_1kRzX8PSoNw2USA</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I wanted to maximize my earnings.</td>\n",
       "      <td>How people think about what they feel in certa...</td>\n",
       "      <td>USA, PA</td>\n",
       "      <td>36</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5306294</th>\n",
       "      <td>9/13/17 11:31</td>\n",
       "      <td>9/13/17 11:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>256</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:35</td>\n",
       "      <td>R_3lAohlIOjmfX3k5</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>From what I have seen in most studies no one g...</td>\n",
       "      <td>Morality</td>\n",
       "      <td>Vermont USA</td>\n",
       "      <td>44</td>\n",
       "      <td>Male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8623697</th>\n",
       "      <td>9/13/17 11:39</td>\n",
       "      <td>9/13/17 11:41</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>126</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 11:41</td>\n",
       "      <td>R_3hDRkTVTxO1olmd</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>There is no reason or incentive to give the bo...</td>\n",
       "      <td>Whether people are likely to give money away t...</td>\n",
       "      <td>OH, USA</td>\n",
       "      <td>30</td>\n",
       "      <td>male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8134166</th>\n",
       "      <td>9/13/17 15:01</td>\n",
       "      <td>9/13/17 15:03</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>113</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 15:03</td>\n",
       "      <td>R_s6V4HtdE4qD17t7</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I'm a greedy bastard, so my natural inclinatio...</td>\n",
       "      <td>I think it's studying human greed.</td>\n",
       "      <td>VA USA</td>\n",
       "      <td>25</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8596815</th>\n",
       "      <td>9/13/17 15:06</td>\n",
       "      <td>9/13/17 15:08</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>112</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 15:08</td>\n",
       "      <td>R_232EPK2fUxbl77l</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I need money</td>\n",
       "      <td>greed</td>\n",
       "      <td>USA PA</td>\n",
       "      <td>27</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6602150</th>\n",
       "      <td>9/13/17 16:12</td>\n",
       "      <td>9/13/17 16:15</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>152</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 16:15</td>\n",
       "      <td>R_1eKp3z27TvT7WQi</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I don't think there is another person</td>\n",
       "      <td>I'm not sure</td>\n",
       "      <td>NY, USA</td>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3473940</th>\n",
       "      <td>9/13/17 16:32</td>\n",
       "      <td>9/13/17 16:34</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>152</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 16:34</td>\n",
       "      <td>R_QoFTmmuZ9XpSU4V</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>My son got tired of giving me money so he did ...</td>\n",
       "      <td>traits of AMT workers</td>\n",
       "      <td>PA, USA</td>\n",
       "      <td>52</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5269230</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>78</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>R_5hvlsH77FVdJIYh</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I work for myself, and don't want to give away...</td>\n",
       "      <td>Charitable behavior.</td>\n",
       "      <td>USA - Pennsylvania</td>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5077941</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>71</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>R_3k7kOJwgYHGeln9</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I wanted to make more money.</td>\n",
       "      <td>generosity and whether people will donate more...</td>\n",
       "      <td>Portland Oregon USA</td>\n",
       "      <td>25</td>\n",
       "      <td>female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6168759</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>86</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>R_AdPRLInN2cVd3nb</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>It's fair and equal.</td>\n",
       "      <td>I'm not sure.  Kindness?</td>\n",
       "      <td>USA, Michigan</td>\n",
       "      <td>30</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6634401</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>R_3fVGV5ZkNuTrHHl</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I wanted to maximize my own bonus.</td>\n",
       "      <td>To see how giving other people are.</td>\n",
       "      <td>California, USA</td>\n",
       "      <td>26</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>Over $100,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6026486</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>91</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_3ndW3UKWnJSDZjH</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Mturk had the most consistent money.  It was i...</td>\n",
       "      <td>Use of mturk vs willingness to give.</td>\n",
       "      <td>Rochester New York, USA</td>\n",
       "      <td>40</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1417422</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>108</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_22Etas0RSwBu4LT</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I have only had luck at mturk</td>\n",
       "      <td>charitable giving responses</td>\n",
       "      <td>USA, Maine</td>\n",
       "      <td>31</td>\n",
       "      <td>Male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5672286</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>93</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_sXpd178WWp5Pufv</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Mostly beneficial to me</td>\n",
       "      <td>generosity of an individual</td>\n",
       "      <td>Massachusetts, USA</td>\n",
       "      <td>32</td>\n",
       "      <td>male</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$80,001 - $100,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5755149</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>131</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_WCf8iglKqxhslH3</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I'm greedy.</td>\n",
       "      <td>Attitudes on generosity.</td>\n",
       "      <td>Texas, USA</td>\n",
       "      <td>25</td>\n",
       "      <td>Female</td>\n",
       "      <td>High school graduate</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>White,Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7287504</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>147</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_bjXB1zGjFGhHbRn</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>because I have worked for mturk since 2015</td>\n",
       "      <td>how people react to different questions</td>\n",
       "      <td>Colorado, USA</td>\n",
       "      <td>33</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6675635</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>163</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_22yanStURNkDQVi</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I like the idea of fairness and karma. I hope ...</td>\n",
       "      <td>What peoples' reasoning for dedicating or not ...</td>\n",
       "      <td>Michigan, USA</td>\n",
       "      <td>31</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7260435</th>\n",
       "      <td>9/13/17 20:35</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>67</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:36</td>\n",
       "      <td>R_CdY8ShpwrwFtgM9</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>i wanted the bonus</td>\n",
       "      <td>unsure</td>\n",
       "      <td>USA GA</td>\n",
       "      <td>22</td>\n",
       "      <td>male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5620933</th>\n",
       "      <td>9/13/17 20:34</td>\n",
       "      <td>9/13/17 20:37</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>175</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:37</td>\n",
       "      <td>R_242XSYOv1tLo5FX</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Money is tight for me right now but I normally...</td>\n",
       "      <td>If people are willing to share</td>\n",
       "      <td>USA, Maryland</td>\n",
       "      <td>27</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1448618</th>\n",
       "      <td>9/18/17 22:45</td>\n",
       "      <td>9/18/17 22:46</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>70</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 22:46</td>\n",
       "      <td>R_2Y3SQjue7Cam7A3</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Basically, I want to maximize my own earnings.</td>\n",
       "      <td>Whether or not I'd share with someone else.</td>\n",
       "      <td>Florida, USA</td>\n",
       "      <td>46</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6407671</th>\n",
       "      <td>9/18/17 22:46</td>\n",
       "      <td>9/18/17 22:51</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>266</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 22:51</td>\n",
       "      <td>R_1o5Ra8DC57qTvZs</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>$1.00 probably doesn't make a big difference t...</td>\n",
       "      <td>How generous people are with \"extra\" money (as...</td>\n",
       "      <td>Pennsylvania, USA</td>\n",
       "      <td>27</td>\n",
       "      <td>Female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8903130</th>\n",
       "      <td>9/18/17 22:51</td>\n",
       "      <td>9/18/17 22:53</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>142</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 22:53</td>\n",
       "      <td>R_veQ4n8R4WzBE945</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>It would be fair to share the bonus between tw...</td>\n",
       "      <td>See how much we are willing to give when we re...</td>\n",
       "      <td>USA Iowa</td>\n",
       "      <td>19</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>under $5,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4390547</th>\n",
       "      <td>9/18/17 22:51</td>\n",
       "      <td>9/18/17 22:56</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>341</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 22:56</td>\n",
       "      <td>R_Wp4kb8GxgS5lhUl</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USA</td>\n",
       "      <td>22</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6606399</th>\n",
       "      <td>9/18/17 22:55</td>\n",
       "      <td>9/18/17 22:59</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>253</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:00</td>\n",
       "      <td>R_3GrffNbuFTfMd7h</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I felt like .80 was still a good pay for the l...</td>\n",
       "      <td>Looking at rationales/choices people make when...</td>\n",
       "      <td>Georgia, USA</td>\n",
       "      <td>27</td>\n",
       "      <td>Female</td>\n",
       "      <td>Professional degree (JD, MD)</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6217626</th>\n",
       "      <td>9/18/17 22:59</td>\n",
       "      <td>9/18/17 23:00</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>93</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:00</td>\n",
       "      <td>R_3pITifJswMTTR3b</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>It just seemed fair</td>\n",
       "      <td>How inclined people are to Altruism with no mo...</td>\n",
       "      <td>PA, USA</td>\n",
       "      <td>44</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4340455</th>\n",
       "      <td>9/18/17 23:02</td>\n",
       "      <td>9/18/17 23:04</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>137</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:04</td>\n",
       "      <td>R_8vHQydiTIMf8Qud</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I felt that I earned the bonus, so why should ...</td>\n",
       "      <td>Altruism</td>\n",
       "      <td>Hawaii, USA</td>\n",
       "      <td>68</td>\n",
       "      <td>Female</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1281714</th>\n",
       "      <td>9/18/17 23:01</td>\n",
       "      <td>9/18/17 23:04</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>185</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:04</td>\n",
       "      <td>R_31T0RWaePKVP9Ur</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>There is no reason to forgo bonuses on Mturk h...</td>\n",
       "      <td>If people are willing to risk a reward for not...</td>\n",
       "      <td>Illinois USA</td>\n",
       "      <td>27</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6195943</th>\n",
       "      <td>9/18/17 23:01</td>\n",
       "      <td>9/18/17 23:05</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>202</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:05</td>\n",
       "      <td>R_3D1m2iYKy3zN0Tg</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I need it all, because we are trying to reach ...</td>\n",
       "      <td>greed</td>\n",
       "      <td>Maine, USA</td>\n",
       "      <td>40</td>\n",
       "      <td>Female</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1347079</th>\n",
       "      <td>9/18/17 23:02</td>\n",
       "      <td>9/18/17 23:06</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>229</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:06</td>\n",
       "      <td>R_2dGR4iCassmZkw9</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I made the choice since I felt I had to give s...</td>\n",
       "      <td>How giving people are willing to give to a ran...</td>\n",
       "      <td>USA, California</td>\n",
       "      <td>33</td>\n",
       "      <td>Male</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5624698</th>\n",
       "      <td>9/18/17 23:02</td>\n",
       "      <td>9/18/17 23:06</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>260</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:06</td>\n",
       "      <td>R_2EBhMhvCtmRKpZR</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I AM IN A POSITION OF NEEDING MONEY RIGHT NOW....</td>\n",
       "      <td>NOT SURE</td>\n",
       "      <td>USA FROM NY LIVING IN FL NOW</td>\n",
       "      <td>35</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1371652</th>\n",
       "      <td>9/18/17 23:04</td>\n",
       "      <td>9/18/17 23:07</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>186</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:07</td>\n",
       "      <td>R_3hlpXjZcvZTURCx</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I did not want to part with all maybe small pe...</td>\n",
       "      <td>Charity?</td>\n",
       "      <td>USA CA</td>\n",
       "      <td>37</td>\n",
       "      <td>Male</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>Over $100,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8682094</th>\n",
       "      <td>9/18/17 23:07</td>\n",
       "      <td>9/18/17 23:08</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:08</td>\n",
       "      <td>R_2rDft7J2tTDEVlk</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I want all the money.</td>\n",
       "      <td>How generous people are</td>\n",
       "      <td>USA, Arizona</td>\n",
       "      <td>25</td>\n",
       "      <td>Male</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7628715</th>\n",
       "      <td>9/18/17 23:02</td>\n",
       "      <td>9/18/17 23:12</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>605</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:12</td>\n",
       "      <td>R_1DtFqiSuzEokLv2</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>i like the gain-gain scheme</td>\n",
       "      <td>NaN</td>\n",
       "      <td>dominican republic, USA</td>\n",
       "      <td>51</td>\n",
       "      <td>male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>Other</td>\n",
       "      <td>latino</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6155410</th>\n",
       "      <td>9/18/17 23:16</td>\n",
       "      <td>9/18/17 23:20</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>245</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:20</td>\n",
       "      <td>R_2Ra0F8Z9Pjdn6JI</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Because I desperately need money, as evidenced...</td>\n",
       "      <td>intelligence</td>\n",
       "      <td>PA, USA</td>\n",
       "      <td>33</td>\n",
       "      <td>male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3537619</th>\n",
       "      <td>9/18/17 23:21</td>\n",
       "      <td>9/18/17 23:24</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>151</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:24</td>\n",
       "      <td>R_3PREyUYYBtYvmPg</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I think it was only fair that I share the bonu...</td>\n",
       "      <td>Not sure</td>\n",
       "      <td>USA-CA</td>\n",
       "      <td>29</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8935588</th>\n",
       "      <td>9/18/17 23:17</td>\n",
       "      <td>9/18/17 23:24</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>426</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:24</td>\n",
       "      <td>R_D94mk6csWmZhzQB</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I was skeptical of whether the random \"worker\"...</td>\n",
       "      <td>People's decision to share resources with peop...</td>\n",
       "      <td>CA, USA</td>\n",
       "      <td>22</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4780052</th>\n",
       "      <td>9/18/17 23:23</td>\n",
       "      <td>9/18/17 23:25</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>111</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:25</td>\n",
       "      <td>R_1K3JGBYURS9SYwX</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Karma</td>\n",
       "      <td>Generosity</td>\n",
       "      <td>USA, Texas</td>\n",
       "      <td>47</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>Over $100,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8104955</th>\n",
       "      <td>9/18/17 23:24</td>\n",
       "      <td>9/18/17 23:26</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>142</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:26</td>\n",
       "      <td>R_yBXG1o0JSyFIjkZ</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I wanted to share something, but I also do thi...</td>\n",
       "      <td>A person's willingness to help others when giv...</td>\n",
       "      <td>CA, USA</td>\n",
       "      <td>44</td>\n",
       "      <td>female</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1250058</th>\n",
       "      <td>9/18/17 23:28</td>\n",
       "      <td>9/18/17 23:29</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>113</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:29</td>\n",
       "      <td>R_3k1xaWKz1Ao9iyS</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I don't know this CrowdFlower worker or what t...</td>\n",
       "      <td>Generosity?</td>\n",
       "      <td>California, USA</td>\n",
       "      <td>27</td>\n",
       "      <td>Male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5012703</th>\n",
       "      <td>9/18/17 23:29</td>\n",
       "      <td>9/18/17 23:35</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>322</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:35</td>\n",
       "      <td>R_2P0x4fUrSbBjTL8</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>It just seemed fair to split the money down th...</td>\n",
       "      <td>I think the study tests how much people are wi...</td>\n",
       "      <td>Texas, USA</td>\n",
       "      <td>41</td>\n",
       "      <td>female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White,American Indian or Alaska Native</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8139784</th>\n",
       "      <td>9/18/17 23:37</td>\n",
       "      <td>9/18/17 23:41</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>256</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:41</td>\n",
       "      <td>R_Bt5loLcKEwAbI77</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>If I donated to everyone, eventually they'd ha...</td>\n",
       "      <td>World and personal views.</td>\n",
       "      <td>Az USA</td>\n",
       "      <td>26</td>\n",
       "      <td>Male</td>\n",
       "      <td>High school graduate</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White,Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7326031</th>\n",
       "      <td>9/18/17 23:39</td>\n",
       "      <td>9/18/17 23:43</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>192</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:43</td>\n",
       "      <td>R_3KrotBcDshzVITT</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>It's nice to share, and though I really need t...</td>\n",
       "      <td>Generosity.</td>\n",
       "      <td>Michigan, USA</td>\n",
       "      <td>36</td>\n",
       "      <td>Cis female</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>under $5,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8473849</th>\n",
       "      <td>9/18/17 22:16</td>\n",
       "      <td>9/19/17 0:03</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>6387</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/19/17 0:03</td>\n",
       "      <td>R_3lG5C315pDR4jxP</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I don't like the other platform.</td>\n",
       "      <td>My willingness to share with other micro platf...</td>\n",
       "      <td>GA, USA</td>\n",
       "      <td>46</td>\n",
       "      <td>Male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8598678</th>\n",
       "      <td>9/19/17 0:44</td>\n",
       "      <td>9/19/17 0:48</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>228</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/19/17 0:48</td>\n",
       "      <td>R_1OP6xjHoIudQQuh</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>This was a super short survey. Most of the sur...</td>\n",
       "      <td>Possibly the generosity of one person to a tot...</td>\n",
       "      <td>USA Tennessee</td>\n",
       "      <td>24</td>\n",
       "      <td>Male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2323555</th>\n",
       "      <td>9/19/17 2:44</td>\n",
       "      <td>9/19/17 2:47</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>181</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/19/17 2:47</td>\n",
       "      <td>R_5aqaGtRcmbbGqml</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>It's mostly arbitrary. Today I don't feel like...</td>\n",
       "      <td>I really don't know anymore.</td>\n",
       "      <td>USA California</td>\n",
       "      <td>33</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2109999</th>\n",
       "      <td>9/19/17 3:03</td>\n",
       "      <td>9/19/17 3:05</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>155</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/19/17 3:05</td>\n",
       "      <td>R_PHhwVTxw2aovpK1</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>It seemed like the first number that popped in...</td>\n",
       "      <td>Altruism.</td>\n",
       "      <td>Illinois, USA</td>\n",
       "      <td>57</td>\n",
       "      <td>Male</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6787973</th>\n",
       "      <td>9/19/17 3:08</td>\n",
       "      <td>9/19/17 3:10</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>114</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/19/17 3:10</td>\n",
       "      <td>R_etckCQZ1M6KpcSR</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I'm greedy</td>\n",
       "      <td>not sure</td>\n",
       "      <td>USA, WV</td>\n",
       "      <td>29</td>\n",
       "      <td>Male</td>\n",
       "      <td>High school graduate</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1475699</th>\n",
       "      <td>9/19/17 3:53</td>\n",
       "      <td>9/19/17 3:55</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>118</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/19/17 3:55</td>\n",
       "      <td>R_1LdmnIMSvSA7IUb</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>I need the money</td>\n",
       "      <td>Not really sure.</td>\n",
       "      <td>NY, USA</td>\n",
       "      <td>46</td>\n",
       "      <td>female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$80,001 - $100,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2329474</th>\n",
       "      <td>9/19/17 4:08</td>\n",
       "      <td>9/19/17 4:13</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>303</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/19/17 4:13</td>\n",
       "      <td>R_22YdzpkYw28LGG2</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>It is a random act of kindness. I want to bles...</td>\n",
       "      <td>No idea generosity?</td>\n",
       "      <td>Texas, USA</td>\n",
       "      <td>50</td>\n",
       "      <td>female</td>\n",
       "      <td>High school graduate</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2510 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               StartDate        EndDate      Status IPAddress Progress  \\\n",
       "mTurkCode                                                                \n",
       "2842236    9/13/17 11:11  9/13/17 11:12  IP Address   *******      100   \n",
       "4563666    9/13/17 11:11  9/13/17 11:12  IP Address   *******      100   \n",
       "6446494    9/13/17 11:11  9/13/17 11:13  IP Address   *******      100   \n",
       "5261906    9/13/17 11:12  9/13/17 11:13  IP Address   *******      100   \n",
       "5520318    9/13/17 11:11  9/13/17 11:13  IP Address   *******      100   \n",
       "2262834    9/13/17 11:11  9/13/17 11:14  IP Address   *******      100   \n",
       "8862928    9/13/17 11:11  9/13/17 11:14  IP Address   *******      100   \n",
       "2120472    9/13/17 11:11  9/13/17 11:14  IP Address   *******      100   \n",
       "5838413    9/13/17 11:13  9/13/17 11:15  IP Address   *******      100   \n",
       "1694952    9/13/17 11:11  9/13/17 11:15  IP Address   *******      100   \n",
       "3533894    9/13/17 11:14  9/13/17 11:16  IP Address   *******      100   \n",
       "7189868    9/13/17 11:21  9/13/17 11:22  IP Address   *******      100   \n",
       "5306294    9/13/17 11:31  9/13/17 11:35  IP Address   *******      100   \n",
       "8623697    9/13/17 11:39  9/13/17 11:41  IP Address   *******      100   \n",
       "8134166    9/13/17 15:01  9/13/17 15:03  IP Address   *******      100   \n",
       "8596815    9/13/17 15:06  9/13/17 15:08  IP Address   *******      100   \n",
       "6602150    9/13/17 16:12  9/13/17 16:15  IP Address   *******      100   \n",
       "3473940    9/13/17 16:32  9/13/17 16:34  IP Address   *******      100   \n",
       "5269230    9/13/17 20:34  9/13/17 20:35  IP Address   *******      100   \n",
       "5077941    9/13/17 20:34  9/13/17 20:35  IP Address   *******      100   \n",
       "6168759    9/13/17 20:34  9/13/17 20:35  IP Address   *******      100   \n",
       "6634401    9/13/17 20:34  9/13/17 20:35  IP Address   *******      100   \n",
       "6026486    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "1417422    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "5672286    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "5755149    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "7287504    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "6675635    9/13/17 20:34  9/13/17 20:36  IP Address   *******      100   \n",
       "7260435    9/13/17 20:35  9/13/17 20:36  IP Address   *******      100   \n",
       "5620933    9/13/17 20:34  9/13/17 20:37  IP Address   *******      100   \n",
       "...                  ...            ...         ...       ...      ...   \n",
       "1448618    9/18/17 22:45  9/18/17 22:46  IP Address   *******      100   \n",
       "6407671    9/18/17 22:46  9/18/17 22:51  IP Address   *******      100   \n",
       "8903130    9/18/17 22:51  9/18/17 22:53  IP Address   *******      100   \n",
       "4390547    9/18/17 22:51  9/18/17 22:56  IP Address   *******      100   \n",
       "6606399    9/18/17 22:55  9/18/17 22:59  IP Address   *******      100   \n",
       "6217626    9/18/17 22:59  9/18/17 23:00  IP Address   *******      100   \n",
       "4340455    9/18/17 23:02  9/18/17 23:04  IP Address   *******      100   \n",
       "1281714    9/18/17 23:01  9/18/17 23:04  IP Address   *******      100   \n",
       "6195943    9/18/17 23:01  9/18/17 23:05  IP Address   *******      100   \n",
       "1347079    9/18/17 23:02  9/18/17 23:06  IP Address   *******      100   \n",
       "5624698    9/18/17 23:02  9/18/17 23:06  IP Address   *******      100   \n",
       "1371652    9/18/17 23:04  9/18/17 23:07  IP Address   *******      100   \n",
       "8682094    9/18/17 23:07  9/18/17 23:08  IP Address   *******      100   \n",
       "7628715    9/18/17 23:02  9/18/17 23:12  IP Address   *******      100   \n",
       "6155410    9/18/17 23:16  9/18/17 23:20  IP Address   *******      100   \n",
       "3537619    9/18/17 23:21  9/18/17 23:24  IP Address   *******      100   \n",
       "8935588    9/18/17 23:17  9/18/17 23:24  IP Address   *******      100   \n",
       "4780052    9/18/17 23:23  9/18/17 23:25  IP Address   *******      100   \n",
       "8104955    9/18/17 23:24  9/18/17 23:26  IP Address   *******      100   \n",
       "1250058    9/18/17 23:28  9/18/17 23:29  IP Address   *******      100   \n",
       "5012703    9/18/17 23:29  9/18/17 23:35  IP Address   *******      100   \n",
       "8139784    9/18/17 23:37  9/18/17 23:41  IP Address   *******      100   \n",
       "7326031    9/18/17 23:39  9/18/17 23:43  IP Address   *******      100   \n",
       "8473849    9/18/17 22:16   9/19/17 0:03  IP Address   *******      100   \n",
       "8598678     9/19/17 0:44   9/19/17 0:48  IP Address   *******      100   \n",
       "2323555     9/19/17 2:44   9/19/17 2:47  IP Address   *******      100   \n",
       "2109999     9/19/17 3:03   9/19/17 3:05  IP Address   *******      100   \n",
       "6787973     9/19/17 3:08   9/19/17 3:10  IP Address   *******      100   \n",
       "1475699     9/19/17 3:53   9/19/17 3:55  IP Address   *******      100   \n",
       "2329474     9/19/17 4:08   9/19/17 4:13  IP Address   *******      100   \n",
       "\n",
       "          Duration (in seconds) Finished   RecordedDate         ResponseId  \\\n",
       "mTurkCode                                                                    \n",
       "2842236                      51     TRUE  9/13/17 11:12  R_vqUgiL0RrIcUZaN   \n",
       "4563666                      47     TRUE  9/13/17 11:12  R_a2A6STjMB7b7LnH   \n",
       "6446494                     112     TRUE  9/13/17 11:13  R_3JwUGrCtLZRT0M0   \n",
       "5261906                      86     TRUE  9/13/17 11:13  R_2Y6f8YlWkL9eYfm   \n",
       "5520318                     133     TRUE  9/13/17 11:13  R_1mwRKmTWSfljrTR   \n",
       "2262834                     138     TRUE  9/13/17 11:14  R_6gRQdDFJJLce1JT   \n",
       "8862928                     160     TRUE  9/13/17 11:14  R_3EEI6vysVLsXxJS   \n",
       "2120472                     168     TRUE  9/13/17 11:14  R_yCmJjtveHIVLkf7   \n",
       "5838413                      89     TRUE  9/13/17 11:15  R_2SH0dL8FYg4ocr5   \n",
       "1694952                     233     TRUE  9/13/17 11:15  R_3EW2IwQIa8KqtRv   \n",
       "3533894                      82     TRUE  9/13/17 11:16  R_ZI7cF6ge94QYSKR   \n",
       "7189868                      78     TRUE  9/13/17 11:22  R_1kRzX8PSoNw2USA   \n",
       "5306294                     256     TRUE  9/13/17 11:35  R_3lAohlIOjmfX3k5   \n",
       "8623697                     126     TRUE  9/13/17 11:41  R_3hDRkTVTxO1olmd   \n",
       "8134166                     113     TRUE  9/13/17 15:03  R_s6V4HtdE4qD17t7   \n",
       "8596815                     112     TRUE  9/13/17 15:08  R_232EPK2fUxbl77l   \n",
       "6602150                     152     TRUE  9/13/17 16:15  R_1eKp3z27TvT7WQi   \n",
       "3473940                     152     TRUE  9/13/17 16:34  R_QoFTmmuZ9XpSU4V   \n",
       "5269230                      78     TRUE  9/13/17 20:35  R_5hvlsH77FVdJIYh   \n",
       "5077941                      71     TRUE  9/13/17 20:35  R_3k7kOJwgYHGeln9   \n",
       "6168759                      86     TRUE  9/13/17 20:35  R_AdPRLInN2cVd3nb   \n",
       "6634401                      75     TRUE  9/13/17 20:35  R_3fVGV5ZkNuTrHHl   \n",
       "6026486                      91     TRUE  9/13/17 20:36  R_3ndW3UKWnJSDZjH   \n",
       "1417422                     108     TRUE  9/13/17 20:36  R_22Etas0RSwBu4LT   \n",
       "5672286                      93     TRUE  9/13/17 20:36  R_sXpd178WWp5Pufv   \n",
       "5755149                     131     TRUE  9/13/17 20:36  R_WCf8iglKqxhslH3   \n",
       "7287504                     147     TRUE  9/13/17 20:36  R_bjXB1zGjFGhHbRn   \n",
       "6675635                     163     TRUE  9/13/17 20:36  R_22yanStURNkDQVi   \n",
       "7260435                      67     TRUE  9/13/17 20:36  R_CdY8ShpwrwFtgM9   \n",
       "5620933                     175     TRUE  9/13/17 20:37  R_242XSYOv1tLo5FX   \n",
       "...                         ...      ...            ...                ...   \n",
       "1448618                      70     TRUE  9/18/17 22:46  R_2Y3SQjue7Cam7A3   \n",
       "6407671                     266     TRUE  9/18/17 22:51  R_1o5Ra8DC57qTvZs   \n",
       "8903130                     142     TRUE  9/18/17 22:53  R_veQ4n8R4WzBE945   \n",
       "4390547                     341     TRUE  9/18/17 22:56  R_Wp4kb8GxgS5lhUl   \n",
       "6606399                     253     TRUE  9/18/17 23:00  R_3GrffNbuFTfMd7h   \n",
       "6217626                      93     TRUE  9/18/17 23:00  R_3pITifJswMTTR3b   \n",
       "4340455                     137     TRUE  9/18/17 23:04  R_8vHQydiTIMf8Qud   \n",
       "1281714                     185     TRUE  9/18/17 23:04  R_31T0RWaePKVP9Ur   \n",
       "6195943                     202     TRUE  9/18/17 23:05  R_3D1m2iYKy3zN0Tg   \n",
       "1347079                     229     TRUE  9/18/17 23:06  R_2dGR4iCassmZkw9   \n",
       "5624698                     260     TRUE  9/18/17 23:06  R_2EBhMhvCtmRKpZR   \n",
       "1371652                     186     TRUE  9/18/17 23:07  R_3hlpXjZcvZTURCx   \n",
       "8682094                      80     TRUE  9/18/17 23:08  R_2rDft7J2tTDEVlk   \n",
       "7628715                     605     TRUE  9/18/17 23:12  R_1DtFqiSuzEokLv2   \n",
       "6155410                     245     TRUE  9/18/17 23:20  R_2Ra0F8Z9Pjdn6JI   \n",
       "3537619                     151     TRUE  9/18/17 23:24  R_3PREyUYYBtYvmPg   \n",
       "8935588                     426     TRUE  9/18/17 23:24  R_D94mk6csWmZhzQB   \n",
       "4780052                     111     TRUE  9/18/17 23:25  R_1K3JGBYURS9SYwX   \n",
       "8104955                     142     TRUE  9/18/17 23:26  R_yBXG1o0JSyFIjkZ   \n",
       "1250058                     113     TRUE  9/18/17 23:29  R_3k1xaWKz1Ao9iyS   \n",
       "5012703                     322     TRUE  9/18/17 23:35  R_2P0x4fUrSbBjTL8   \n",
       "8139784                     256     TRUE  9/18/17 23:41  R_Bt5loLcKEwAbI77   \n",
       "7326031                     192     TRUE  9/18/17 23:43  R_3KrotBcDshzVITT   \n",
       "8473849                    6387     TRUE   9/19/17 0:03  R_3lG5C315pDR4jxP   \n",
       "8598678                     228     TRUE   9/19/17 0:48  R_1OP6xjHoIudQQuh   \n",
       "2323555                     181     TRUE   9/19/17 2:47  R_5aqaGtRcmbbGqml   \n",
       "2109999                     155     TRUE   9/19/17 3:05  R_PHhwVTxw2aovpK1   \n",
       "6787973                     114     TRUE   9/19/17 3:10  R_etckCQZ1M6KpcSR   \n",
       "1475699                     118     TRUE   9/19/17 3:55  R_1LdmnIMSvSA7IUb   \n",
       "2329474                     303     TRUE   9/19/17 4:13  R_22YdzpkYw28LGG2   \n",
       "\n",
       "          RecipientLastName        ...         \\\n",
       "mTurkCode                          ...          \n",
       "2842236             *******        ...          \n",
       "4563666             *******        ...          \n",
       "6446494             *******        ...          \n",
       "5261906             *******        ...          \n",
       "5520318             *******        ...          \n",
       "2262834             *******        ...          \n",
       "8862928             *******        ...          \n",
       "2120472             *******        ...          \n",
       "5838413             *******        ...          \n",
       "1694952             *******        ...          \n",
       "3533894             *******        ...          \n",
       "7189868             *******        ...          \n",
       "5306294             *******        ...          \n",
       "8623697             *******        ...          \n",
       "8134166             *******        ...          \n",
       "8596815             *******        ...          \n",
       "6602150             *******        ...          \n",
       "3473940             *******        ...          \n",
       "5269230             *******        ...          \n",
       "5077941             *******        ...          \n",
       "6168759             *******        ...          \n",
       "6634401             *******        ...          \n",
       "6026486             *******        ...          \n",
       "1417422             *******        ...          \n",
       "5672286             *******        ...          \n",
       "5755149             *******        ...          \n",
       "7287504             *******        ...          \n",
       "6675635             *******        ...          \n",
       "7260435             *******        ...          \n",
       "5620933             *******        ...          \n",
       "...                     ...        ...          \n",
       "1448618             *******        ...          \n",
       "6407671             *******        ...          \n",
       "8903130             *******        ...          \n",
       "4390547             *******        ...          \n",
       "6606399             *******        ...          \n",
       "6217626             *******        ...          \n",
       "4340455             *******        ...          \n",
       "1281714             *******        ...          \n",
       "6195943             *******        ...          \n",
       "1347079             *******        ...          \n",
       "5624698             *******        ...          \n",
       "1371652             *******        ...          \n",
       "8682094             *******        ...          \n",
       "7628715             *******        ...          \n",
       "6155410             *******        ...          \n",
       "3537619             *******        ...          \n",
       "8935588             *******        ...          \n",
       "4780052             *******        ...          \n",
       "8104955             *******        ...          \n",
       "1250058             *******        ...          \n",
       "5012703             *******        ...          \n",
       "8139784             *******        ...          \n",
       "7326031             *******        ...          \n",
       "8473849             *******        ...          \n",
       "8598678             *******        ...          \n",
       "2323555             *******        ...          \n",
       "2109999             *******        ...          \n",
       "6787973             *******        ...          \n",
       "1475699             *******        ...          \n",
       "2329474             *******        ...          \n",
       "\n",
       "                                                    strategy  \\\n",
       "mTurkCode                                                      \n",
       "2842236                                         I want money   \n",
       "4563666                 I wanted to maximize my own earnings   \n",
       "6446494                                 I want my max bonus.   \n",
       "5261906                                              i dunno   \n",
       "5520318                 Give something back to the platform    \n",
       "2262834    I was sick of working for other people who did...   \n",
       "8862928                                     for extra income   \n",
       "2120472                    I didn't want to destroy anything   \n",
       "5838413    I don't know the other person and I might need...   \n",
       "1694952    I needed extra money since I am a student and ...   \n",
       "3533894    I was not sure how legitimate it was so i gave...   \n",
       "7189868                    I wanted to maximize my earnings.   \n",
       "5306294    From what I have seen in most studies no one g...   \n",
       "8623697    There is no reason or incentive to give the bo...   \n",
       "8134166    I'm a greedy bastard, so my natural inclinatio...   \n",
       "8596815                                         I need money   \n",
       "6602150                I don't think there is another person   \n",
       "3473940    My son got tired of giving me money so he did ...   \n",
       "5269230    I work for myself, and don't want to give away...   \n",
       "5077941                         I wanted to make more money.   \n",
       "6168759                                 It's fair and equal.   \n",
       "6634401                   I wanted to maximize my own bonus.   \n",
       "6026486    Mturk had the most consistent money.  It was i...   \n",
       "1417422                        I have only had luck at mturk   \n",
       "5672286                              Mostly beneficial to me   \n",
       "5755149                                          I'm greedy.   \n",
       "7287504           because I have worked for mturk since 2015   \n",
       "6675635    I like the idea of fairness and karma. I hope ...   \n",
       "7260435                                   i wanted the bonus   \n",
       "5620933    Money is tight for me right now but I normally...   \n",
       "...                                                      ...   \n",
       "1448618       Basically, I want to maximize my own earnings.   \n",
       "6407671    $1.00 probably doesn't make a big difference t...   \n",
       "8903130    It would be fair to share the bonus between tw...   \n",
       "4390547                                                  NaN   \n",
       "6606399    I felt like .80 was still a good pay for the l...   \n",
       "6217626                                  It just seemed fair   \n",
       "4340455    I felt that I earned the bonus, so why should ...   \n",
       "1281714    There is no reason to forgo bonuses on Mturk h...   \n",
       "6195943    I need it all, because we are trying to reach ...   \n",
       "1347079    I made the choice since I felt I had to give s...   \n",
       "5624698    I AM IN A POSITION OF NEEDING MONEY RIGHT NOW....   \n",
       "1371652    I did not want to part with all maybe small pe...   \n",
       "8682094                                I want all the money.   \n",
       "7628715                          i like the gain-gain scheme   \n",
       "6155410    Because I desperately need money, as evidenced...   \n",
       "3537619    I think it was only fair that I share the bonu...   \n",
       "8935588    I was skeptical of whether the random \"worker\"...   \n",
       "4780052                                                Karma   \n",
       "8104955    I wanted to share something, but I also do thi...   \n",
       "1250058    I don't know this CrowdFlower worker or what t...   \n",
       "5012703    It just seemed fair to split the money down th...   \n",
       "8139784    If I donated to everyone, eventually they'd ha...   \n",
       "7326031    It's nice to share, and though I really need t...   \n",
       "8473849                    I don't like the other platform.    \n",
       "8598678    This was a super short survey. Most of the sur...   \n",
       "2323555    It's mostly arbitrary. Today I don't feel like...   \n",
       "2109999    It seemed like the first number that popped in...   \n",
       "6787973                                           I'm greedy   \n",
       "1475699                                     I need the money   \n",
       "2329474    It is a random act of kindness. I want to bles...   \n",
       "\n",
       "                                             experimentAbout  \\\n",
       "mTurkCode                                                      \n",
       "2842236                                            who cares   \n",
       "4563666                                         I don't know   \n",
       "6446494    To see how much people are willing to help oth...   \n",
       "5261906                                                  NaN   \n",
       "5520318                                          Perception    \n",
       "2262834                                     I have no idea.    \n",
       "8862928                                             not sure   \n",
       "2120472                                       I have no idea   \n",
       "5838413                                          Generosity    \n",
       "1694952                                           Not sure.    \n",
       "3533894                                      our generosity.   \n",
       "7189868    How people think about what they feel in certa...   \n",
       "5306294                                            Morality    \n",
       "8623697    Whether people are likely to give money away t...   \n",
       "8134166                  I think it's studying human greed.    \n",
       "8596815                                                greed   \n",
       "6602150                                         I'm not sure   \n",
       "3473940                                traits of AMT workers   \n",
       "5269230                                 Charitable behavior.   \n",
       "5077941    generosity and whether people will donate more...   \n",
       "6168759                             I'm not sure.  Kindness?   \n",
       "6634401                  To see how giving other people are.   \n",
       "6026486               Use of mturk vs willingness to give.     \n",
       "1417422                          charitable giving responses   \n",
       "5672286                          generosity of an individual   \n",
       "5755149                             Attitudes on generosity.   \n",
       "7287504              how people react to different questions   \n",
       "6675635    What peoples' reasoning for dedicating or not ...   \n",
       "7260435                                               unsure   \n",
       "5620933                       If people are willing to share   \n",
       "...                                                      ...   \n",
       "1448618          Whether or not I'd share with someone else.   \n",
       "6407671    How generous people are with \"extra\" money (as...   \n",
       "8903130    See how much we are willing to give when we re...   \n",
       "4390547                                                  NaN   \n",
       "6606399    Looking at rationales/choices people make when...   \n",
       "6217626    How inclined people are to Altruism with no mo...   \n",
       "4340455                                             Altruism   \n",
       "1281714    If people are willing to risk a reward for not...   \n",
       "6195943                                                greed   \n",
       "1347079    How giving people are willing to give to a ran...   \n",
       "5624698                                             NOT SURE   \n",
       "1371652                                             Charity?   \n",
       "8682094                              How generous people are   \n",
       "7628715                                                  NaN   \n",
       "6155410                                         intelligence   \n",
       "3537619                                             Not sure   \n",
       "8935588    People's decision to share resources with peop...   \n",
       "4780052                                           Generosity   \n",
       "8104955    A person's willingness to help others when giv...   \n",
       "1250058                                          Generosity?   \n",
       "5012703    I think the study tests how much people are wi...   \n",
       "8139784                            World and personal views.   \n",
       "7326031                                         Generosity.    \n",
       "8473849    My willingness to share with other micro platf...   \n",
       "8598678    Possibly the generosity of one person to a tot...   \n",
       "2323555                         I really don't know anymore.   \n",
       "2109999                                            Altruism.   \n",
       "6787973                                             not sure   \n",
       "1475699                                     Not really sure.   \n",
       "2329474                                  No idea generosity?   \n",
       "\n",
       "                               location age          sex  \\\n",
       "mTurkCode                                                  \n",
       "2842236                             USA  25         male   \n",
       "4563666                   Virginia, USA  27         Male   \n",
       "6446494                         CA, USA  21         Male   \n",
       "5261906                         USA, wa  26       female   \n",
       "5520318                    USA Indiana   29         Male   \n",
       "2262834                  Wisconsin, USA  35         Male   \n",
       "8862928                          USA TN  49       Female   \n",
       "2120472                             USA  38       female   \n",
       "5838413                         MO, USA  26       female   \n",
       "1694952                         WA, USA  21       Female   \n",
       "3533894                   USA Wisconsin  30         male   \n",
       "7189868                         USA, PA  36         male   \n",
       "5306294                     Vermont USA  44        Male    \n",
       "8623697                         OH, USA  30         male   \n",
       "8134166                          VA USA  25         Male   \n",
       "8596815                          USA PA  27         male   \n",
       "6602150                         NY, USA  27         Male   \n",
       "3473940                         PA, USA  52       female   \n",
       "5269230              USA - Pennsylvania  27         Male   \n",
       "5077941             Portland Oregon USA  25       female   \n",
       "6168759                   USA, Michigan  30       Female   \n",
       "6634401                 California, USA  26         Male   \n",
       "6026486         Rochester New York, USA  40         Male   \n",
       "1417422                      USA, Maine  31         Male   \n",
       "5672286              Massachusetts, USA  32         male   \n",
       "5755149                      Texas, USA  25       Female   \n",
       "7287504                   Colorado, USA  33       Female   \n",
       "6675635                   Michigan, USA  31       Female   \n",
       "7260435                          USA GA  22         male   \n",
       "5620933                   USA, Maryland  27       female   \n",
       "...                                 ...  ..          ...   \n",
       "1448618                    Florida, USA  46         male   \n",
       "6407671               Pennsylvania, USA  27       Female   \n",
       "8903130                        USA Iowa  19         Male   \n",
       "4390547                             USA  22         Male   \n",
       "6606399                    Georgia, USA  27       Female   \n",
       "6217626                         PA, USA  44       female   \n",
       "4340455                     Hawaii, USA  68       Female   \n",
       "1281714                    Illinois USA  27         male   \n",
       "6195943                      Maine, USA  40       Female   \n",
       "1347079                 USA, California  33         Male   \n",
       "5624698    USA FROM NY LIVING IN FL NOW  35       FEMALE   \n",
       "1371652                          USA CA  37         Male   \n",
       "8682094                    USA, Arizona  25         Male   \n",
       "7628715         dominican republic, USA  51         male   \n",
       "6155410                         PA, USA  33         male   \n",
       "3537619                          USA-CA  29         Male   \n",
       "8935588                         CA, USA  22         Male   \n",
       "4780052                      USA, Texas  47         Male   \n",
       "8104955                         CA, USA  44       female   \n",
       "1250058                 California, USA  27         Male   \n",
       "5012703                      Texas, USA  41       female   \n",
       "8139784                          Az USA  26         Male   \n",
       "7326031                   Michigan, USA  36  Cis female    \n",
       "8473849                         GA, USA  46         Male   \n",
       "8598678                   USA Tennessee  24         Male   \n",
       "2323555                  USA California  33         male   \n",
       "2109999                   Illinois, USA  57         Male   \n",
       "6787973                         USA, WV  29         Male   \n",
       "1475699                         NY, USA  46       female   \n",
       "2329474                      Texas, USA  50       female   \n",
       "\n",
       "                                       education                 Q32  \\\n",
       "mTurkCode                                                              \n",
       "2842236    Bachelor's degree in college (4-year)   $25,001 - $35,000   \n",
       "4563666               Some college but no degree   $15,001 - $25,000   \n",
       "6446494     Associate degree in college (2-year)   $15,001 - $25,000   \n",
       "5261906               Some college but no degree        under $5,000   \n",
       "5520318    Bachelor's degree in college (4-year)   $65,001 - $80,000   \n",
       "2262834    Bachelor's degree in college (4-year)   $25,001 - $35,000   \n",
       "8862928               Some college but no degree  $50,001 -  $65,000   \n",
       "2120472               Some college but no degree   $65,001 - $80,000   \n",
       "5838413                     High school graduate   $25,001 - $35,000   \n",
       "1694952               Some college but no degree        under $5,000   \n",
       "3533894    Bachelor's degree in college (4-year)  $80,001 - $100,000   \n",
       "7189868    Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "5306294     Associate degree in college (2-year)   $25,001 - $35,000   \n",
       "8623697     Associate degree in college (2-year)   $15,001 - $25,000   \n",
       "8134166    Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "8596815    Bachelor's degree in college (4-year)    $5,000 - $10,000   \n",
       "6602150               Some college but no degree  $50,001 -  $65,000   \n",
       "3473940               Some college but no degree   $10,001 - $15,000   \n",
       "5269230                          Master's degree   $25,001 - $35,000   \n",
       "5077941    Bachelor's degree in college (4-year)   $10,001 - $15,000   \n",
       "6168759               Some college but no degree   $15,001 - $25,000   \n",
       "6634401    Bachelor's degree in college (4-year)       Over $100,000   \n",
       "6026486    Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "1417422     Associate degree in college (2-year)   $65,001 - $80,000   \n",
       "5672286                          Master's degree  $80,001 - $100,000   \n",
       "5755149                     High school graduate   $10,001 - $15,000   \n",
       "7287504               Some college but no degree  $50,001 -  $65,000   \n",
       "6675635               Some college but no degree    $5,000 - $10,000   \n",
       "7260435               Some college but no degree   $25,001 - $35,000   \n",
       "5620933               Some college but no degree    $5,000 - $10,000   \n",
       "...                                          ...                 ...   \n",
       "1448618    Bachelor's degree in college (4-year)   $65,001 - $80,000   \n",
       "6407671    Bachelor's degree in college (4-year)   $25,001 - $35,000   \n",
       "8903130               Some college but no degree        under $5,000   \n",
       "4390547               Some college but no degree    $5,000 - $10,000   \n",
       "6606399             Professional degree (JD, MD)   $35,001 - $50,000   \n",
       "6217626               Some college but no degree   $25,001 - $35,000   \n",
       "4340455     Associate degree in college (2-year)   $65,001 - $80,000   \n",
       "1281714    Bachelor's degree in college (4-year)   $35,001 - $50,000   \n",
       "6195943     Associate degree in college (2-year)   $35,001 - $50,000   \n",
       "1347079                          Master's degree    $5,000 - $10,000   \n",
       "5624698               Some college but no degree   $15,001 - $25,000   \n",
       "1371652                          Master's degree       Over $100,000   \n",
       "8682094                          Master's degree  $50,001 -  $65,000   \n",
       "7628715               Some college but no degree   $15,001 - $25,000   \n",
       "6155410               Some college but no degree   $15,001 - $25,000   \n",
       "3537619    Bachelor's degree in college (4-year)   $15,001 - $25,000   \n",
       "8935588               Some college but no degree   $10,001 - $15,000   \n",
       "4780052               Some college but no degree       Over $100,000   \n",
       "8104955     Associate degree in college (2-year)   $25,001 - $35,000   \n",
       "1250058     Associate degree in college (2-year)   $65,001 - $80,000   \n",
       "5012703    Bachelor's degree in college (4-year)   $15,001 - $25,000   \n",
       "8139784                     High school graduate   $15,001 - $25,000   \n",
       "7326031     Associate degree in college (2-year)        under $5,000   \n",
       "8473849     Associate degree in college (2-year)  $50,001 -  $65,000   \n",
       "8598678     Associate degree in college (2-year)   $10,001 - $15,000   \n",
       "2323555    Bachelor's degree in college (4-year)   $25,001 - $35,000   \n",
       "2109999                          Master's degree   $65,001 - $80,000   \n",
       "6787973                     High school graduate   $15,001 - $25,000   \n",
       "1475699    Bachelor's degree in college (4-year)  $80,001 - $100,000   \n",
       "2329474                     High school graduate    $5,000 - $10,000   \n",
       "\n",
       "                                             race race_6_TEXT  \\\n",
       "mTurkCode                                                       \n",
       "2842236                                     White         NaN   \n",
       "4563666                                     White         NaN   \n",
       "6446494                                     White         NaN   \n",
       "5261906                                     White         NaN   \n",
       "5520318                                     White         NaN   \n",
       "2262834                                     White         NaN   \n",
       "8862928                                     White         NaN   \n",
       "2120472                                     White         NaN   \n",
       "5838413                                     White         NaN   \n",
       "1694952                                     White         NaN   \n",
       "3533894                                     White         NaN   \n",
       "7189868                                     White         NaN   \n",
       "5306294                                     White         NaN   \n",
       "8623697                                     White         NaN   \n",
       "8134166                                     Asian         NaN   \n",
       "8596815                                     White         NaN   \n",
       "6602150                 Black or African American         NaN   \n",
       "3473940                                     White         NaN   \n",
       "5269230                                     White         NaN   \n",
       "5077941                                     White         NaN   \n",
       "6168759                                     White         NaN   \n",
       "6634401                                     White         NaN   \n",
       "6026486                                     White         NaN   \n",
       "1417422                                     White         NaN   \n",
       "5672286                                     Asian         NaN   \n",
       "5755149           White,Black or African American         NaN   \n",
       "7287504                                     White         NaN   \n",
       "6675635                                     White         NaN   \n",
       "7260435                 Black or African American         NaN   \n",
       "5620933                 Black or African American         NaN   \n",
       "...                                           ...         ...   \n",
       "1448618                                     White         NaN   \n",
       "6407671                                     White         NaN   \n",
       "8903130                                     Asian         NaN   \n",
       "4390547                                     Asian         NaN   \n",
       "6606399                                     White         NaN   \n",
       "6217626                                     White         NaN   \n",
       "4340455                                     White         NaN   \n",
       "1281714                                     Asian         NaN   \n",
       "6195943                                     White         NaN   \n",
       "1347079                                     White         NaN   \n",
       "5624698                                     White         NaN   \n",
       "1371652                                     Asian         NaN   \n",
       "8682094                                     White         NaN   \n",
       "7628715                                     Other      latino   \n",
       "6155410                                     White         NaN   \n",
       "3537619                                     Asian         NaN   \n",
       "8935588                                     Asian         NaN   \n",
       "4780052                                     White         NaN   \n",
       "8104955                                     White         NaN   \n",
       "1250058                                     White         NaN   \n",
       "5012703    White,American Indian or Alaska Native         NaN   \n",
       "8139784           White,Black or African American         NaN   \n",
       "7326031                                     White         NaN   \n",
       "8473849                 Black or African American         NaN   \n",
       "8598678                                     White         NaN   \n",
       "2323555                                     White         NaN   \n",
       "2109999                                     White         NaN   \n",
       "6787973                                     White         NaN   \n",
       "1475699                                     White         NaN   \n",
       "2329474                                     White         NaN   \n",
       "\n",
       "          strategy - Topics  \n",
       "mTurkCode                    \n",
       "2842236                 NaN  \n",
       "4563666                 NaN  \n",
       "6446494                 NaN  \n",
       "5261906                 NaN  \n",
       "5520318                 NaN  \n",
       "2262834                 NaN  \n",
       "8862928                 NaN  \n",
       "2120472                 NaN  \n",
       "5838413                 NaN  \n",
       "1694952                 NaN  \n",
       "3533894                 NaN  \n",
       "7189868                 NaN  \n",
       "5306294                 NaN  \n",
       "8623697                 NaN  \n",
       "8134166                 NaN  \n",
       "8596815                 NaN  \n",
       "6602150                 NaN  \n",
       "3473940                 NaN  \n",
       "5269230                 NaN  \n",
       "5077941                 NaN  \n",
       "6168759                 NaN  \n",
       "6634401                 NaN  \n",
       "6026486                 NaN  \n",
       "1417422                 NaN  \n",
       "5672286                 NaN  \n",
       "5755149                 NaN  \n",
       "7287504                 NaN  \n",
       "6675635                 NaN  \n",
       "7260435                 NaN  \n",
       "5620933                 NaN  \n",
       "...                     ...  \n",
       "1448618                 NaN  \n",
       "6407671                 NaN  \n",
       "8903130                 NaN  \n",
       "4390547                 NaN  \n",
       "6606399                 NaN  \n",
       "6217626                 NaN  \n",
       "4340455                 NaN  \n",
       "1281714                 NaN  \n",
       "6195943                 NaN  \n",
       "1347079                 NaN  \n",
       "5624698                 NaN  \n",
       "1371652                 NaN  \n",
       "8682094                 NaN  \n",
       "7628715                 NaN  \n",
       "6155410                 NaN  \n",
       "3537619                 NaN  \n",
       "8935588                 NaN  \n",
       "4780052                 NaN  \n",
       "8104955                 NaN  \n",
       "1250058                 NaN  \n",
       "5012703                 NaN  \n",
       "8139784                 NaN  \n",
       "7326031                 NaN  \n",
       "8473849                 NaN  \n",
       "8598678                 NaN  \n",
       "2323555                 NaN  \n",
       "2109999                 NaN  \n",
       "6787973                 NaN  \n",
       "1475699                 NaN  \n",
       "2329474                 NaN  \n",
       "\n",
       "[2510 rows x 37 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[df.Finished==\"TRUE\"]\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p><strong>Only take the first 2500</strong> participants as per our pre-registeration</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(df.index[2500:])\n",
    "df\n",
    "#to make the search faster\n",
    "data = df.to_dict(orient='index')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculating the bonus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>StartDate</th>\n",
       "      <th>EndDate</th>\n",
       "      <th>Status</th>\n",
       "      <th>IPAddress</th>\n",
       "      <th>Progress</th>\n",
       "      <th>Duration (in seconds)</th>\n",
       "      <th>Finished</th>\n",
       "      <th>RecordedDate</th>\n",
       "      <th>ResponseId</th>\n",
       "      <th>RecipientLastName</th>\n",
       "      <th>...</th>\n",
       "      <th>location</th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>education</th>\n",
       "      <th>Q32</th>\n",
       "      <th>race</th>\n",
       "      <th>race_6_TEXT</th>\n",
       "      <th>strategy - Topics</th>\n",
       "      <th>treatment</th>\n",
       "      <th>valid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1001123</th>\n",
       "      <td>9/17/17 23:36</td>\n",
       "      <td>9/17/17 23:39</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>222</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 23:39</td>\n",
       "      <td>R_Z30QZLSwRtC0JYl</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA, CA</td>\n",
       "      <td>28</td>\n",
       "      <td>Female</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>Native Hawaiian or Pacific Islander</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1001888</th>\n",
       "      <td>9/18/17 10:50</td>\n",
       "      <td>9/18/17 10:53</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>182</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 10:53</td>\n",
       "      <td>R_zeyYKtbcrsrOcnL</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>SOUTH CAROLINA, USA</td>\n",
       "      <td>52</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1004332</th>\n",
       "      <td>9/15/17 9:44</td>\n",
       "      <td>9/15/17 9:46</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>107</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 9:46</td>\n",
       "      <td>R_RKvhwuW5klFGIz7</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA Virginia</td>\n",
       "      <td>22</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>under $5,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1008852</th>\n",
       "      <td>9/17/17 18:05</td>\n",
       "      <td>9/17/17 18:08</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>213</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 18:08</td>\n",
       "      <td>R_VPa9y7DmPUeBXot</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA, North Carolina</td>\n",
       "      <td>33</td>\n",
       "      <td>Female</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1009339</th>\n",
       "      <td>9/13/17 22:04</td>\n",
       "      <td>9/13/17 22:08</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>243</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 22:08</td>\n",
       "      <td>R_WigWVTLv1UZqvkZ</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Tennessee USA</td>\n",
       "      <td>55</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$80,001 - $100,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1009556</th>\n",
       "      <td>9/15/17 15:14</td>\n",
       "      <td>9/15/17 15:15</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>71</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 15:15</td>\n",
       "      <td>R_1kOm41rWqXpypRL</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA, fl</td>\n",
       "      <td>50</td>\n",
       "      <td>female</td>\n",
       "      <td>Professional degree (JD, MD)</td>\n",
       "      <td>under $5,000</td>\n",
       "      <td>Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1012744</th>\n",
       "      <td>9/18/17 0:47</td>\n",
       "      <td>9/18/17 0:51</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>257</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 0:51</td>\n",
       "      <td>R_b48quKGdmDeCYLL</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA, Kansas</td>\n",
       "      <td>37</td>\n",
       "      <td>Female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1013582</th>\n",
       "      <td>9/14/17 21:22</td>\n",
       "      <td>9/14/17 21:24</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>125</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/14/17 21:24</td>\n",
       "      <td>R_3M5ta7zUv43x61y</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA South Carolina</td>\n",
       "      <td>28</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1019069</th>\n",
       "      <td>9/15/17 10:50</td>\n",
       "      <td>9/15/17 10:52</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>98</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 10:52</td>\n",
       "      <td>R_DBSrPmxjWQcOJVv</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA</td>\n",
       "      <td>35</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1020947</th>\n",
       "      <td>9/14/17 6:01</td>\n",
       "      <td>9/14/17 6:04</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>191</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/14/17 6:04</td>\n",
       "      <td>R_2AFOtTJlIY0fDLw</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Florida, USA</td>\n",
       "      <td>27</td>\n",
       "      <td>Female</td>\n",
       "      <td>High school graduate</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1022969</th>\n",
       "      <td>9/15/17 7:59</td>\n",
       "      <td>9/15/17 8:03</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>216</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 8:03</td>\n",
       "      <td>R_BJHPemkOgEDOSrf</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Missouri, USA</td>\n",
       "      <td>39</td>\n",
       "      <td>female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>under $5,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1025406</th>\n",
       "      <td>9/15/17 7:01</td>\n",
       "      <td>9/15/17 7:07</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>369</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 7:07</td>\n",
       "      <td>R_p5HCKc7f0OARtFn</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA N.Y.</td>\n",
       "      <td>31</td>\n",
       "      <td>Male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>Native Hawaiian or Pacific Islander</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1034992</th>\n",
       "      <td>9/15/17 9:43</td>\n",
       "      <td>9/15/17 9:46</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>182</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 9:46</td>\n",
       "      <td>R_2P5mrEsLJJjN41J</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Virginia, USA</td>\n",
       "      <td>31</td>\n",
       "      <td>Female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1035488</th>\n",
       "      <td>9/17/17 17:44</td>\n",
       "      <td>9/17/17 17:45</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>64</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 17:45</td>\n",
       "      <td>R_2pY9mj8CI5UZVRt</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>CA, USA</td>\n",
       "      <td>28</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>Over $100,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1038138</th>\n",
       "      <td>9/17/17 17:59</td>\n",
       "      <td>9/17/17 18:01</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>143</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 18:01</td>\n",
       "      <td>R_yOPzUO8PbE4uPsJ</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA Texas</td>\n",
       "      <td>33</td>\n",
       "      <td>female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1038378</th>\n",
       "      <td>9/17/17 18:20</td>\n",
       "      <td>9/17/17 18:22</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>127</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 18:22</td>\n",
       "      <td>R_3nox0ODtah3rIeV</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NY , USA</td>\n",
       "      <td>41</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1043506</th>\n",
       "      <td>9/15/17 10:43</td>\n",
       "      <td>9/15/17 10:47</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>223</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 10:47</td>\n",
       "      <td>R_27lZe7JrGeBkIP7</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Spokane, WA USA</td>\n",
       "      <td>47</td>\n",
       "      <td>male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1044313</th>\n",
       "      <td>9/18/17 8:00</td>\n",
       "      <td>9/18/17 8:02</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>106</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 8:02</td>\n",
       "      <td>R_3EgmsyQ2WvYYMs9</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Pennsylvania, USA</td>\n",
       "      <td>34</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1045417</th>\n",
       "      <td>9/14/17 14:00</td>\n",
       "      <td>9/14/17 14:01</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>74</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/14/17 14:01</td>\n",
       "      <td>R_DkkSOlsgtnOVJN7</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>New York, United States</td>\n",
       "      <td>37</td>\n",
       "      <td>Female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1052729</th>\n",
       "      <td>9/17/17 17:45</td>\n",
       "      <td>9/17/17 17:54</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>494</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 17:54</td>\n",
       "      <td>R_2xRVTbcw64LyeYU</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA</td>\n",
       "      <td>52</td>\n",
       "      <td>Male</td>\n",
       "      <td>Doctoral degree</td>\n",
       "      <td>under $5,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1052959</th>\n",
       "      <td>9/18/17 21:02</td>\n",
       "      <td>9/18/17 21:04</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 21:04</td>\n",
       "      <td>R_1QsbJKepju9Qmna</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>CA, USA</td>\n",
       "      <td>30</td>\n",
       "      <td>male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1058756</th>\n",
       "      <td>9/17/17 18:04</td>\n",
       "      <td>9/17/17 18:07</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>174</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 18:07</td>\n",
       "      <td>R_2E7a0R2G3bVwQri</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Texas - USA</td>\n",
       "      <td>24</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White,Other</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1058900</th>\n",
       "      <td>9/18/17 8:12</td>\n",
       "      <td>9/18/17 8:14</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>114</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 8:14</td>\n",
       "      <td>R_1gnjQPPhoU7nCbI</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Portland Maine USA</td>\n",
       "      <td>33</td>\n",
       "      <td>female</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1060092</th>\n",
       "      <td>9/14/17 19:03</td>\n",
       "      <td>9/14/17 19:06</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>175</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/14/17 19:06</td>\n",
       "      <td>R_28XUK9qBw70wetz</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Tamarac, FL USA</td>\n",
       "      <td>30</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1066093</th>\n",
       "      <td>9/14/17 6:01</td>\n",
       "      <td>9/14/17 6:04</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>212</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/14/17 6:04</td>\n",
       "      <td>R_2VxVR6zmPqjzxam</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Illinois, USA</td>\n",
       "      <td>63</td>\n",
       "      <td>Female</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1068815</th>\n",
       "      <td>9/15/17 9:53</td>\n",
       "      <td>9/15/17 9:57</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>233</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 9:57</td>\n",
       "      <td>R_9tA1JVpI3yAPpMB</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA Illinois</td>\n",
       "      <td>28</td>\n",
       "      <td>Female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1073711</th>\n",
       "      <td>9/13/17 20:46</td>\n",
       "      <td>9/13/17 20:47</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>69</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/13/17 20:47</td>\n",
       "      <td>R_1FK6EqjOmH3Zhg1</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Louisiana, USA</td>\n",
       "      <td>26</td>\n",
       "      <td>Male</td>\n",
       "      <td>High school graduate</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1074289</th>\n",
       "      <td>9/14/17 15:39</td>\n",
       "      <td>9/14/17 15:40</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>57</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/14/17 15:40</td>\n",
       "      <td>R_NUrlfSY2hbi3M6R</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA WA</td>\n",
       "      <td>28</td>\n",
       "      <td>MALE</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T4</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1075064</th>\n",
       "      <td>9/17/17 17:55</td>\n",
       "      <td>9/17/17 17:57</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>133</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 17:58</td>\n",
       "      <td>R_56zjR7ApdhONFuN</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>usa</td>\n",
       "      <td>55</td>\n",
       "      <td>F</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1075722</th>\n",
       "      <td>9/18/17 9:41</td>\n",
       "      <td>9/18/17 9:44</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>201</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 9:44</td>\n",
       "      <td>R_3kGqwR5f6maqsUX</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA, NY</td>\n",
       "      <td>27</td>\n",
       "      <td>MALE</td>\n",
       "      <td>Professional degree (JD, MD)</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>Other</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8912039</th>\n",
       "      <td>9/15/17 2:36</td>\n",
       "      <td>9/15/17 2:37</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>74</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 2:37</td>\n",
       "      <td>R_1CDBMW76HDNxQ2E</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>PA USA</td>\n",
       "      <td>24</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8915831</th>\n",
       "      <td>9/15/17 7:54</td>\n",
       "      <td>9/15/17 7:56</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>147</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 7:56</td>\n",
       "      <td>R_yrpXI3WhkToXmnv</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>texas, usa</td>\n",
       "      <td>39</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8924767</th>\n",
       "      <td>9/15/17 7:36</td>\n",
       "      <td>9/15/17 7:38</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>110</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 7:38</td>\n",
       "      <td>R_1N4dxRoZgofq8K4</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA, New York</td>\n",
       "      <td>34</td>\n",
       "      <td>Male</td>\n",
       "      <td>Professional degree (JD, MD)</td>\n",
       "      <td>Over $100,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8926768</th>\n",
       "      <td>9/18/17 21:40</td>\n",
       "      <td>9/18/17 21:42</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>123</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 21:42</td>\n",
       "      <td>R_0uihu2GwFj2hRoR</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA - Texas</td>\n",
       "      <td>35</td>\n",
       "      <td>male</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8928657</th>\n",
       "      <td>9/18/17 16:05</td>\n",
       "      <td>9/18/17 16:07</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>155</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 16:07</td>\n",
       "      <td>R_3lAjbJB2mFazFrJ</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NM USA</td>\n",
       "      <td>59</td>\n",
       "      <td>male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White,American Indian or Alaska Native</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8930123</th>\n",
       "      <td>9/14/17 15:35</td>\n",
       "      <td>9/14/17 15:37</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>122</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/14/17 15:37</td>\n",
       "      <td>R_3isALY4CzHwelYZ</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA- Honolulu, Hawaii</td>\n",
       "      <td>28</td>\n",
       "      <td>female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8935588</th>\n",
       "      <td>9/18/17 23:17</td>\n",
       "      <td>9/18/17 23:24</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>426</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 23:24</td>\n",
       "      <td>R_D94mk6csWmZhzQB</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>CA, USA</td>\n",
       "      <td>22</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8940115</th>\n",
       "      <td>9/15/17 7:04</td>\n",
       "      <td>9/15/17 7:08</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>239</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 7:08</td>\n",
       "      <td>R_27vU54gdbeUoKCU</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Alabama USA</td>\n",
       "      <td>56</td>\n",
       "      <td>female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8946401</th>\n",
       "      <td>9/17/17 17:20</td>\n",
       "      <td>9/17/17 17:21</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>96</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 17:21</td>\n",
       "      <td>R_OkX83CWvyJlBs5z</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NJ, USA</td>\n",
       "      <td>36</td>\n",
       "      <td>female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$65,001 - $80,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8946697</th>\n",
       "      <td>9/15/17 7:11</td>\n",
       "      <td>9/15/17 7:13</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>115</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 7:13</td>\n",
       "      <td>R_2V9MczmSQKPHNUO</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA, Colorado</td>\n",
       "      <td>29</td>\n",
       "      <td>male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8949788</th>\n",
       "      <td>9/15/17 7:56</td>\n",
       "      <td>9/15/17 8:03</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>442</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 8:03</td>\n",
       "      <td>R_2dW9oBP5xRgz9NN</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Columbia, South Carolina, USA</td>\n",
       "      <td>35</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T4</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8953783</th>\n",
       "      <td>9/15/17 7:19</td>\n",
       "      <td>9/15/17 7:21</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>156</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 7:21</td>\n",
       "      <td>R_1DvVrb00OhPhpeg</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA Michigan</td>\n",
       "      <td>37</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T4</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8955564</th>\n",
       "      <td>9/15/17 10:44</td>\n",
       "      <td>9/15/17 10:46</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>105</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 10:46</td>\n",
       "      <td>R_1qakRORt3XzdpWP</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA, CALIFORNIA</td>\n",
       "      <td>28</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8957763</th>\n",
       "      <td>9/18/17 7:40</td>\n",
       "      <td>9/18/17 7:45</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>269</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 7:45</td>\n",
       "      <td>R_DHJx2kfMYAkVVa9</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA</td>\n",
       "      <td>38</td>\n",
       "      <td>female</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>Over $100,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T4</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8961273</th>\n",
       "      <td>9/14/17 5:48</td>\n",
       "      <td>9/14/17 5:50</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>154</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/14/17 5:50</td>\n",
       "      <td>R_1OH4rtCcFqbtHOT</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>New York City USA</td>\n",
       "      <td>48</td>\n",
       "      <td>female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$80,001 - $100,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8963814</th>\n",
       "      <td>9/17/17 17:20</td>\n",
       "      <td>9/17/17 17:22</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>142</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 17:22</td>\n",
       "      <td>R_3hDCRrm4bztVb0a</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Michigan, USA</td>\n",
       "      <td>29</td>\n",
       "      <td>Female</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8968341</th>\n",
       "      <td>9/18/17 12:03</td>\n",
       "      <td>9/18/17 12:06</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>206</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 12:06</td>\n",
       "      <td>R_2rN2NBds1IeaNEk</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA South Carolina</td>\n",
       "      <td>33</td>\n",
       "      <td>Male</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T4</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8968877</th>\n",
       "      <td>9/15/17 6:59</td>\n",
       "      <td>9/15/17 7:01</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>125</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 7:01</td>\n",
       "      <td>R_AnRic2nmYigtAVr</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>NC, USA</td>\n",
       "      <td>27</td>\n",
       "      <td>male</td>\n",
       "      <td>High school graduate</td>\n",
       "      <td>$15,001 - $25,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8970580</th>\n",
       "      <td>9/17/17 17:37</td>\n",
       "      <td>9/17/17 17:38</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>93</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 17:38</td>\n",
       "      <td>R_BzXf6KHE5DA59bb</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA</td>\n",
       "      <td>21</td>\n",
       "      <td>female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>Other</td>\n",
       "      <td>west indian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8971952</th>\n",
       "      <td>9/18/17 15:16</td>\n",
       "      <td>9/18/17 15:18</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>162</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 15:19</td>\n",
       "      <td>R_241uY0YNZI8lgPd</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Oklahoma, USA</td>\n",
       "      <td>26</td>\n",
       "      <td>nonbinary, assigned female at birth</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>under $5,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8976374</th>\n",
       "      <td>9/17/17 23:27</td>\n",
       "      <td>9/17/17 23:30</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>219</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 23:30</td>\n",
       "      <td>R_UmgKvt5VdijvvgZ</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA, North Carolina</td>\n",
       "      <td>23</td>\n",
       "      <td>Female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8976994</th>\n",
       "      <td>9/17/17 17:39</td>\n",
       "      <td>9/17/17 17:41</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>99</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 17:41</td>\n",
       "      <td>R_80uwiQCyH9nQ5QR</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Utah, USA</td>\n",
       "      <td>34</td>\n",
       "      <td>Female</td>\n",
       "      <td>Some college but no degree</td>\n",
       "      <td>$80,001 - $100,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8977962</th>\n",
       "      <td>9/15/17 7:11</td>\n",
       "      <td>9/15/17 7:12</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>88</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 7:12</td>\n",
       "      <td>R_2R1xlYfSOnYbiXk</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA WA</td>\n",
       "      <td>36</td>\n",
       "      <td>f</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$5,000 - $10,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8978123</th>\n",
       "      <td>9/14/17 7:23</td>\n",
       "      <td>9/14/17 7:24</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/14/17 7:24</td>\n",
       "      <td>R_tFX2Df9mvs2zmMh</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>GA, USA.</td>\n",
       "      <td>25</td>\n",
       "      <td>Male</td>\n",
       "      <td>Associate degree in college (2-year)</td>\n",
       "      <td>$10,001 - $15,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8982508</th>\n",
       "      <td>9/17/17 18:01</td>\n",
       "      <td>9/17/17 18:04</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>154</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/17/17 18:04</td>\n",
       "      <td>R_301MMfwKWJgeoIK</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>nj, usa</td>\n",
       "      <td>24</td>\n",
       "      <td>male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>Over $100,000</td>\n",
       "      <td>Asian</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8984036</th>\n",
       "      <td>9/18/17 8:30</td>\n",
       "      <td>9/18/17 8:32</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>156</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 8:33</td>\n",
       "      <td>R_At8gXoccYsvlDZD</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Louisiana, USA</td>\n",
       "      <td>33</td>\n",
       "      <td>Female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8986182</th>\n",
       "      <td>9/14/17 6:23</td>\n",
       "      <td>9/14/17 6:27</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>262</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/14/17 6:27</td>\n",
       "      <td>R_2axyD7lOOw0moXj</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Minnesota,USA</td>\n",
       "      <td>28</td>\n",
       "      <td>Female</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>Over $100,000</td>\n",
       "      <td>Black or African American</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8995691</th>\n",
       "      <td>9/14/17 6:24</td>\n",
       "      <td>9/14/17 7:08</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>2600</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/14/17 7:08</td>\n",
       "      <td>R_1hPVqDa4udJjD8H</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>Oklahoma USA</td>\n",
       "      <td>32</td>\n",
       "      <td>female</td>\n",
       "      <td>High school graduate</td>\n",
       "      <td>$35,001 - $50,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T4</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8995859</th>\n",
       "      <td>9/18/17 13:31</td>\n",
       "      <td>9/18/17 13:34</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>175</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/18/17 13:34</td>\n",
       "      <td>R_3sCQZA0LHyVn8dP</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA</td>\n",
       "      <td>28</td>\n",
       "      <td>Male</td>\n",
       "      <td>Bachelor's degree in college (4-year)</td>\n",
       "      <td>$25,001 - $35,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T3</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8999156</th>\n",
       "      <td>9/15/17 7:58</td>\n",
       "      <td>9/15/17 7:59</td>\n",
       "      <td>IP Address</td>\n",
       "      <td>*******</td>\n",
       "      <td>100</td>\n",
       "      <td>99</td>\n",
       "      <td>TRUE</td>\n",
       "      <td>9/15/17 7:59</td>\n",
       "      <td>R_2YEr9786DdZTSIw</td>\n",
       "      <td>*******</td>\n",
       "      <td>...</td>\n",
       "      <td>USA KY</td>\n",
       "      <td>45</td>\n",
       "      <td>male</td>\n",
       "      <td>Master's degree</td>\n",
       "      <td>$50,001 -  $65,000</td>\n",
       "      <td>White</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>T1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2500 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             StartDate        EndDate      Status IPAddress Progress  \\\n",
       "1001123  9/17/17 23:36  9/17/17 23:39  IP Address   *******      100   \n",
       "1001888  9/18/17 10:50  9/18/17 10:53  IP Address   *******      100   \n",
       "1004332   9/15/17 9:44   9/15/17 9:46  IP Address   *******      100   \n",
       "1008852  9/17/17 18:05  9/17/17 18:08  IP Address   *******      100   \n",
       "1009339  9/13/17 22:04  9/13/17 22:08  IP Address   *******      100   \n",
       "1009556  9/15/17 15:14  9/15/17 15:15  IP Address   *******      100   \n",
       "1012744   9/18/17 0:47   9/18/17 0:51  IP Address   *******      100   \n",
       "1013582  9/14/17 21:22  9/14/17 21:24  IP Address   *******      100   \n",
       "1019069  9/15/17 10:50  9/15/17 10:52  IP Address   *******      100   \n",
       "1020947   9/14/17 6:01   9/14/17 6:04  IP Address   *******      100   \n",
       "1022969   9/15/17 7:59   9/15/17 8:03  IP Address   *******      100   \n",
       "1025406   9/15/17 7:01   9/15/17 7:07  IP Address   *******      100   \n",
       "1034992   9/15/17 9:43   9/15/17 9:46  IP Address   *******      100   \n",
       "1035488  9/17/17 17:44  9/17/17 17:45  IP Address   *******      100   \n",
       "1038138  9/17/17 17:59  9/17/17 18:01  IP Address   *******      100   \n",
       "1038378  9/17/17 18:20  9/17/17 18:22  IP Address   *******      100   \n",
       "1043506  9/15/17 10:43  9/15/17 10:47  IP Address   *******      100   \n",
       "1044313   9/18/17 8:00   9/18/17 8:02  IP Address   *******      100   \n",
       "1045417  9/14/17 14:00  9/14/17 14:01  IP Address   *******      100   \n",
       "1052729  9/17/17 17:45  9/17/17 17:54  IP Address   *******      100   \n",
       "1052959  9/18/17 21:02  9/18/17 21:04  IP Address   *******      100   \n",
       "1058756  9/17/17 18:04  9/17/17 18:07  IP Address   *******      100   \n",
       "1058900   9/18/17 8:12   9/18/17 8:14  IP Address   *******      100   \n",
       "1060092  9/14/17 19:03  9/14/17 19:06  IP Address   *******      100   \n",
       "1066093   9/14/17 6:01   9/14/17 6:04  IP Address   *******      100   \n",
       "1068815   9/15/17 9:53   9/15/17 9:57  IP Address   *******      100   \n",
       "1073711  9/13/17 20:46  9/13/17 20:47  IP Address   *******      100   \n",
       "1074289  9/14/17 15:39  9/14/17 15:40  IP Address   *******      100   \n",
       "1075064  9/17/17 17:55  9/17/17 17:57  IP Address   *******      100   \n",
       "1075722   9/18/17 9:41   9/18/17 9:44  IP Address   *******      100   \n",
       "...                ...            ...         ...       ...      ...   \n",
       "8912039   9/15/17 2:36   9/15/17 2:37  IP Address   *******      100   \n",
       "8915831   9/15/17 7:54   9/15/17 7:56  IP Address   *******      100   \n",
       "8924767   9/15/17 7:36   9/15/17 7:38  IP Address   *******      100   \n",
       "8926768  9/18/17 21:40  9/18/17 21:42  IP Address   *******      100   \n",
       "8928657  9/18/17 16:05  9/18/17 16:07  IP Address   *******      100   \n",
       "8930123  9/14/17 15:35  9/14/17 15:37  IP Address   *******      100   \n",
       "8935588  9/18/17 23:17  9/18/17 23:24  IP Address   *******      100   \n",
       "8940115   9/15/17 7:04   9/15/17 7:08  IP Address   *******      100   \n",
       "8946401  9/17/17 17:20  9/17/17 17:21  IP Address   *******      100   \n",
       "8946697   9/15/17 7:11   9/15/17 7:13  IP Address   *******      100   \n",
       "8949788   9/15/17 7:56   9/15/17 8:03  IP Address   *******      100   \n",
       "8953783   9/15/17 7:19   9/15/17 7:21  IP Address   *******      100   \n",
       "8955564  9/15/17 10:44  9/15/17 10:46  IP Address   *******      100   \n",
       "8957763   9/18/17 7:40   9/18/17 7:45  IP Address   *******      100   \n",
       "8961273   9/14/17 5:48   9/14/17 5:50  IP Address   *******      100   \n",
       "8963814  9/17/17 17:20  9/17/17 17:22  IP Address   *******      100   \n",
       "8968341  9/18/17 12:03  9/18/17 12:06  IP Address   *******      100   \n",
       "8968877   9/15/17 6:59   9/15/17 7:01  IP Address   *******      100   \n",
       "8970580  9/17/17 17:37  9/17/17 17:38  IP Address   *******      100   \n",
       "8971952  9/18/17 15:16  9/18/17 15:18  IP Address   *******      100   \n",
       "8976374  9/17/17 23:27  9/17/17 23:30  IP Address   *******      100   \n",
       "8976994  9/17/17 17:39  9/17/17 17:41  IP Address   *******      100   \n",
       "8977962   9/15/17 7:11   9/15/17 7:12  IP Address   *******      100   \n",
       "8978123   9/14/17 7:23   9/14/17 7:24  IP Address   *******      100   \n",
       "8982508  9/17/17 18:01  9/17/17 18:04  IP Address   *******      100   \n",
       "8984036   9/18/17 8:30   9/18/17 8:32  IP Address   *******      100   \n",
       "8986182   9/14/17 6:23   9/14/17 6:27  IP Address   *******      100   \n",
       "8995691   9/14/17 6:24   9/14/17 7:08  IP Address   *******      100   \n",
       "8995859  9/18/17 13:31  9/18/17 13:34  IP Address   *******      100   \n",
       "8999156   9/15/17 7:58   9/15/17 7:59  IP Address   *******      100   \n",
       "\n",
       "        Duration (in seconds) Finished   RecordedDate         ResponseId  \\\n",
       "1001123                   222     TRUE  9/17/17 23:39  R_Z30QZLSwRtC0JYl   \n",
       "1001888                   182     TRUE  9/18/17 10:53  R_zeyYKtbcrsrOcnL   \n",
       "1004332                   107     TRUE   9/15/17 9:46  R_RKvhwuW5klFGIz7   \n",
       "1008852                   213     TRUE  9/17/17 18:08  R_VPa9y7DmPUeBXot   \n",
       "1009339                   243     TRUE  9/13/17 22:08  R_WigWVTLv1UZqvkZ   \n",
       "1009556                    71     TRUE  9/15/17 15:15  R_1kOm41rWqXpypRL   \n",
       "1012744                   257     TRUE   9/18/17 0:51  R_b48quKGdmDeCYLL   \n",
       "1013582                   125     TRUE  9/14/17 21:24  R_3M5ta7zUv43x61y   \n",
       "1019069                    98     TRUE  9/15/17 10:52  R_DBSrPmxjWQcOJVv   \n",
       "1020947                   191     TRUE   9/14/17 6:04  R_2AFOtTJlIY0fDLw   \n",
       "1022969                   216     TRUE   9/15/17 8:03  R_BJHPemkOgEDOSrf   \n",
       "1025406                   369     TRUE   9/15/17 7:07  R_p5HCKc7f0OARtFn   \n",
       "1034992                   182     TRUE   9/15/17 9:46  R_2P5mrEsLJJjN41J   \n",
       "1035488                    64     TRUE  9/17/17 17:45  R_2pY9mj8CI5UZVRt   \n",
       "1038138                   143     TRUE  9/17/17 18:01  R_yOPzUO8PbE4uPsJ   \n",
       "1038378                   127     TRUE  9/17/17 18:22  R_3nox0ODtah3rIeV   \n",
       "1043506                   223     TRUE  9/15/17 10:47  R_27lZe7JrGeBkIP7   \n",
       "1044313                   106     TRUE   9/18/17 8:02  R_3EgmsyQ2WvYYMs9   \n",
       "1045417                    74     TRUE  9/14/17 14:01  R_DkkSOlsgtnOVJN7   \n",
       "1052729                   494     TRUE  9/17/17 17:54  R_2xRVTbcw64LyeYU   \n",
       "1052959                   123     TRUE  9/18/17 21:04  R_1QsbJKepju9Qmna   \n",
       "1058756                   174     TRUE  9/17/17 18:07  R_2E7a0R2G3bVwQri   \n",
       "1058900                   114     TRUE   9/18/17 8:14  R_1gnjQPPhoU7nCbI   \n",
       "1060092                   175     TRUE  9/14/17 19:06  R_28XUK9qBw70wetz   \n",
       "1066093                   212     TRUE   9/14/17 6:04  R_2VxVR6zmPqjzxam   \n",
       "1068815                   233     TRUE   9/15/17 9:57  R_9tA1JVpI3yAPpMB   \n",
       "1073711                    69     TRUE  9/13/17 20:47  R_1FK6EqjOmH3Zhg1   \n",
       "1074289                    57     TRUE  9/14/17 15:40  R_NUrlfSY2hbi3M6R   \n",
       "1075064                   133     TRUE  9/17/17 17:58  R_56zjR7ApdhONFuN   \n",
       "1075722                   201     TRUE   9/18/17 9:44  R_3kGqwR5f6maqsUX   \n",
       "...                       ...      ...            ...                ...   \n",
       "8912039                    74     TRUE   9/15/17 2:37  R_1CDBMW76HDNxQ2E   \n",
       "8915831                   147     TRUE   9/15/17 7:56  R_yrpXI3WhkToXmnv   \n",
       "8924767                   110     TRUE   9/15/17 7:38  R_1N4dxRoZgofq8K4   \n",
       "8926768                   123     TRUE  9/18/17 21:42  R_0uihu2GwFj2hRoR   \n",
       "8928657                   155     TRUE  9/18/17 16:07  R_3lAjbJB2mFazFrJ   \n",
       "8930123                   122     TRUE  9/14/17 15:37  R_3isALY4CzHwelYZ   \n",
       "8935588                   426     TRUE  9/18/17 23:24  R_D94mk6csWmZhzQB   \n",
       "8940115                   239     TRUE   9/15/17 7:08  R_27vU54gdbeUoKCU   \n",
       "8946401                    96     TRUE  9/17/17 17:21  R_OkX83CWvyJlBs5z   \n",
       "8946697                   115     TRUE   9/15/17 7:13  R_2V9MczmSQKPHNUO   \n",
       "8949788                   442     TRUE   9/15/17 8:03  R_2dW9oBP5xRgz9NN   \n",
       "8953783                   156     TRUE   9/15/17 7:21  R_1DvVrb00OhPhpeg   \n",
       "8955564                   105     TRUE  9/15/17 10:46  R_1qakRORt3XzdpWP   \n",
       "8957763                   269     TRUE   9/18/17 7:45  R_DHJx2kfMYAkVVa9   \n",
       "8961273                   154     TRUE   9/14/17 5:50  R_1OH4rtCcFqbtHOT   \n",
       "8963814                   142     TRUE  9/17/17 17:22  R_3hDCRrm4bztVb0a   \n",
       "8968341                   206     TRUE  9/18/17 12:06  R_2rN2NBds1IeaNEk   \n",
       "8968877                   125     TRUE   9/15/17 7:01  R_AnRic2nmYigtAVr   \n",
       "8970580                    93     TRUE  9/17/17 17:38  R_BzXf6KHE5DA59bb   \n",
       "8971952                   162     TRUE  9/18/17 15:19  R_241uY0YNZI8lgPd   \n",
       "8976374                   219     TRUE  9/17/17 23:30  R_UmgKvt5VdijvvgZ   \n",
       "8976994                    99     TRUE  9/17/17 17:41  R_80uwiQCyH9nQ5QR   \n",
       "8977962                    88     TRUE   9/15/17 7:12  R_2R1xlYfSOnYbiXk   \n",
       "8978123                   100     TRUE   9/14/17 7:24  R_tFX2Df9mvs2zmMh   \n",
       "8982508                   154     TRUE  9/17/17 18:04  R_301MMfwKWJgeoIK   \n",
       "8984036                   156     TRUE   9/18/17 8:33  R_At8gXoccYsvlDZD   \n",
       "8986182                   262     TRUE   9/14/17 6:27  R_2axyD7lOOw0moXj   \n",
       "8995691                  2600     TRUE   9/14/17 7:08  R_1hPVqDa4udJjD8H   \n",
       "8995859                   175     TRUE  9/18/17 13:34  R_3sCQZA0LHyVn8dP   \n",
       "8999156                    99     TRUE   9/15/17 7:59  R_2YEr9786DdZTSIw   \n",
       "\n",
       "        RecipientLastName  ...                         location age  \\\n",
       "1001123           *******  ...                          USA, CA  28   \n",
       "1001888           *******  ...              SOUTH CAROLINA, USA  52   \n",
       "1004332           *******  ...                     USA Virginia  22   \n",
       "1008852           *******  ...              USA, North Carolina  33   \n",
       "1009339           *******  ...                    Tennessee USA  55   \n",
       "1009556           *******  ...                          USA, fl  50   \n",
       "1012744           *******  ...                      USA, Kansas  37   \n",
       "1013582           *******  ...               USA South Carolina  28   \n",
       "1019069           *******  ...                              USA  35   \n",
       "1020947           *******  ...                     Florida, USA  27   \n",
       "1022969           *******  ...                    Missouri, USA  39   \n",
       "1025406           *******  ...                         USA N.Y.  31   \n",
       "1034992           *******  ...                    Virginia, USA  31   \n",
       "1035488           *******  ...                          CA, USA  28   \n",
       "1038138           *******  ...                        USA Texas  33   \n",
       "1038378           *******  ...                         NY , USA  41   \n",
       "1043506           *******  ...                  Spokane, WA USA  47   \n",
       "1044313           *******  ...                Pennsylvania, USA  34   \n",
       "1045417           *******  ...          New York, United States  37   \n",
       "1052729           *******  ...                              USA  52   \n",
       "1052959           *******  ...                          CA, USA  30   \n",
       "1058756           *******  ...                      Texas - USA  24   \n",
       "1058900           *******  ...               Portland Maine USA  33   \n",
       "1060092           *******  ...                 Tamarac, FL USA   30   \n",
       "1066093           *******  ...                    Illinois, USA  63   \n",
       "1068815           *******  ...                     USA Illinois  28   \n",
       "1073711           *******  ...                   Louisiana, USA  26   \n",
       "1074289           *******  ...                           USA WA  28   \n",
       "1075064           *******  ...                              usa  55   \n",
       "1075722           *******  ...                          USA, NY  27   \n",
       "...                   ...  ...                              ...  ..   \n",
       "8912039           *******  ...                           PA USA  24   \n",
       "8915831           *******  ...                       texas, usa  39   \n",
       "8924767           *******  ...                    USA, New York  34   \n",
       "8926768           *******  ...                      USA - Texas  35   \n",
       "8928657           *******  ...                           NM USA  59   \n",
       "8930123           *******  ...            USA- Honolulu, Hawaii  28   \n",
       "8935588           *******  ...                          CA, USA  22   \n",
       "8940115           *******  ...                      Alabama USA  56   \n",
       "8946401           *******  ...                          NJ, USA  36   \n",
       "8946697           *******  ...                    USA, Colorado  29   \n",
       "8949788           *******  ...    Columbia, South Carolina, USA  35   \n",
       "8953783           *******  ...                     USA Michigan  37   \n",
       "8955564           *******  ...                  USA, CALIFORNIA  28   \n",
       "8957763           *******  ...                              USA  38   \n",
       "8961273           *******  ...                New York City USA  48   \n",
       "8963814           *******  ...                    Michigan, USA  29   \n",
       "8968341           *******  ...              USA South Carolina   33   \n",
       "8968877           *******  ...                          NC, USA  27   \n",
       "8970580           *******  ...                              USA  21   \n",
       "8971952           *******  ...                    Oklahoma, USA  26   \n",
       "8976374           *******  ...              USA, North Carolina  23   \n",
       "8976994           *******  ...                        Utah, USA  34   \n",
       "8977962           *******  ...                           USA WA  36   \n",
       "8978123           *******  ...                        GA, USA.   25   \n",
       "8982508           *******  ...                          nj, usa  24   \n",
       "8984036           *******  ...                   Louisiana, USA  33   \n",
       "8986182           *******  ...                    Minnesota,USA  28   \n",
       "8995691           *******  ...                     Oklahoma USA  32   \n",
       "8995859           *******  ...                              USA  28   \n",
       "8999156           *******  ...                           USA KY  45   \n",
       "\n",
       "                                         sex  \\\n",
       "1001123                               Female   \n",
       "1001888                               FEMALE   \n",
       "1004332                                 Male   \n",
       "1008852                               Female   \n",
       "1009339                               Female   \n",
       "1009556                               female   \n",
       "1012744                               Female   \n",
       "1013582                                 Male   \n",
       "1019069                                 Male   \n",
       "1020947                               Female   \n",
       "1022969                               female   \n",
       "1025406                                 Male   \n",
       "1034992                               Female   \n",
       "1035488                                 male   \n",
       "1038138                               female   \n",
       "1038378                                 male   \n",
       "1043506                                 male   \n",
       "1044313                                 Male   \n",
       "1045417                               Female   \n",
       "1052729                                 Male   \n",
       "1052959                                 male   \n",
       "1058756                                 Male   \n",
       "1058900                               female   \n",
       "1060092                                 Male   \n",
       "1066093                               Female   \n",
       "1068815                               Female   \n",
       "1073711                                 Male   \n",
       "1074289                                 MALE   \n",
       "1075064                                    F   \n",
       "1075722                                 MALE   \n",
       "...                                      ...   \n",
       "8912039                                 Male   \n",
       "8915831                                 male   \n",
       "8924767                                 Male   \n",
       "8926768                                 male   \n",
       "8928657                                 male   \n",
       "8930123                               female   \n",
       "8935588                                 Male   \n",
       "8940115                               female   \n",
       "8946401                               female   \n",
       "8946697                                 male   \n",
       "8949788                               Female   \n",
       "8953783                               Female   \n",
       "8955564                               female   \n",
       "8957763                               female   \n",
       "8961273                               female   \n",
       "8963814                               Female   \n",
       "8968341                                 Male   \n",
       "8968877                                 male   \n",
       "8970580                               female   \n",
       "8971952  nonbinary, assigned female at birth   \n",
       "8976374                               Female   \n",
       "8976994                               Female   \n",
       "8977962                                    f   \n",
       "8978123                                 Male   \n",
       "8982508                                 male   \n",
       "8984036                               Female   \n",
       "8986182                               Female   \n",
       "8995691                               female   \n",
       "8995859                                 Male   \n",
       "8999156                                 male   \n",
       "\n",
       "                                     education                 Q32  \\\n",
       "1001123                        Master's degree   $35,001 - $50,000   \n",
       "1001888  Bachelor's degree in college (4-year)   $65,001 - $80,000   \n",
       "1004332             Some college but no degree        under $5,000   \n",
       "1008852   Associate degree in college (2-year)   $15,001 - $25,000   \n",
       "1009339             Some college but no degree  $80,001 - $100,000   \n",
       "1009556           Professional degree (JD, MD)        under $5,000   \n",
       "1012744  Bachelor's degree in college (4-year)    $5,000 - $10,000   \n",
       "1013582             Some college but no degree   $15,001 - $25,000   \n",
       "1019069  Bachelor's degree in college (4-year)   $65,001 - $80,000   \n",
       "1020947                   High school graduate   $35,001 - $50,000   \n",
       "1022969  Bachelor's degree in college (4-year)        under $5,000   \n",
       "1025406   Associate degree in college (2-year)   $25,001 - $35,000   \n",
       "1034992  Bachelor's degree in college (4-year)   $15,001 - $25,000   \n",
       "1035488  Bachelor's degree in college (4-year)       Over $100,000   \n",
       "1038138  Bachelor's degree in college (4-year)   $15,001 - $25,000   \n",
       "1038378  Bachelor's degree in college (4-year)   $65,001 - $80,000   \n",
       "1043506   Associate degree in college (2-year)   $25,001 - $35,000   \n",
       "1044313  Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "1045417  Bachelor's degree in college (4-year)   $25,001 - $35,000   \n",
       "1052729                        Doctoral degree        under $5,000   \n",
       "1052959   Associate degree in college (2-year)    $5,000 - $10,000   \n",
       "1058756  Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "1058900                        Master's degree   $35,001 - $50,000   \n",
       "1060092             Some college but no degree   $35,001 - $50,000   \n",
       "1066093   Associate degree in college (2-year)  $50,001 -  $65,000   \n",
       "1068815  Bachelor's degree in college (4-year)   $65,001 - $80,000   \n",
       "1073711                   High school graduate   $25,001 - $35,000   \n",
       "1074289  Bachelor's degree in college (4-year)   $25,001 - $35,000   \n",
       "1075064             Some college but no degree   $35,001 - $50,000   \n",
       "1075722           Professional degree (JD, MD)   $15,001 - $25,000   \n",
       "...                                        ...                 ...   \n",
       "8912039             Some college but no degree    $5,000 - $10,000   \n",
       "8915831  Bachelor's degree in college (4-year)   $35,001 - $50,000   \n",
       "8924767           Professional degree (JD, MD)       Over $100,000   \n",
       "8926768                        Master's degree   $35,001 - $50,000   \n",
       "8928657             Some college but no degree   $15,001 - $25,000   \n",
       "8930123  Bachelor's degree in college (4-year)   $15,001 - $25,000   \n",
       "8935588             Some college but no degree   $10,001 - $15,000   \n",
       "8940115  Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "8946401  Bachelor's degree in college (4-year)   $65,001 - $80,000   \n",
       "8946697   Associate degree in college (2-year)    $5,000 - $10,000   \n",
       "8949788             Some college but no degree   $35,001 - $50,000   \n",
       "8953783             Some college but no degree   $15,001 - $25,000   \n",
       "8955564             Some college but no degree   $15,001 - $25,000   \n",
       "8957763                        Master's degree       Over $100,000   \n",
       "8961273  Bachelor's degree in college (4-year)  $80,001 - $100,000   \n",
       "8963814   Associate degree in college (2-year)  $50,001 -  $65,000   \n",
       "8968341             Some college but no degree   $15,001 - $25,000   \n",
       "8968877                   High school graduate   $15,001 - $25,000   \n",
       "8970580             Some college but no degree   $35,001 - $50,000   \n",
       "8971952  Bachelor's degree in college (4-year)        under $5,000   \n",
       "8976374  Bachelor's degree in college (4-year)   $35,001 - $50,000   \n",
       "8976994             Some college but no degree  $80,001 - $100,000   \n",
       "8977962  Bachelor's degree in college (4-year)    $5,000 - $10,000   \n",
       "8978123   Associate degree in college (2-year)   $10,001 - $15,000   \n",
       "8982508  Bachelor's degree in college (4-year)       Over $100,000   \n",
       "8984036  Bachelor's degree in college (4-year)  $50,001 -  $65,000   \n",
       "8986182  Bachelor's degree in college (4-year)       Over $100,000   \n",
       "8995691                   High school graduate   $35,001 - $50,000   \n",
       "8995859  Bachelor's degree in college (4-year)   $25,001 - $35,000   \n",
       "8999156                        Master's degree  $50,001 -  $65,000   \n",
       "\n",
       "                                           race  race_6_TEXT  \\\n",
       "1001123     Native Hawaiian or Pacific Islander          NaN   \n",
       "1001888                                   White          NaN   \n",
       "1004332                                   White          NaN   \n",
       "1008852                                   White          NaN   \n",
       "1009339                                   Asian          NaN   \n",
       "1009556               Black or African American          NaN   \n",
       "1012744                                   White          NaN   \n",
       "1013582                                   White          NaN   \n",
       "1019069                                   White          NaN   \n",
       "1020947                                   White          NaN   \n",
       "1022969                                   White          NaN   \n",
       "1025406     Native Hawaiian or Pacific Islander          NaN   \n",
       "1034992                                   White          NaN   \n",
       "1035488                                   White          NaN   \n",
       "1038138                                   White          NaN   \n",
       "1038378                                   White          NaN   \n",
       "1043506                                   White          NaN   \n",
       "1044313                                   White          NaN   \n",
       "1045417                                   White          NaN   \n",
       "1052729                                   White          NaN   \n",
       "1052959                                   White          NaN   \n",
       "1058756                             White,Other     Hispanic   \n",
       "1058900                                   White          NaN   \n",
       "1060092                                   White          NaN   \n",
       "1066093                                   White          NaN   \n",
       "1068815                                   White          NaN   \n",
       "1073711                                   White          NaN   \n",
       "1074289                                   White          NaN   \n",
       "1075064                                   White          NaN   \n",
       "1075722                                   Other     Hispanic   \n",
       "...                                         ...          ...   \n",
       "8912039                                   White          NaN   \n",
       "8915831                                   White          NaN   \n",
       "8924767                                   White          NaN   \n",
       "8926768                                   White          NaN   \n",
       "8928657  White,American Indian or Alaska Native          NaN   \n",
       "8930123                                   Asian          NaN   \n",
       "8935588                                   Asian          NaN   \n",
       "8940115               Black or African American          NaN   \n",
       "8946401                                   White          NaN   \n",
       "8946697                                   White          NaN   \n",
       "8949788                                   White          NaN   \n",
       "8953783                                   White          NaN   \n",
       "8955564                                   White          NaN   \n",
       "8957763                                   White          NaN   \n",
       "8961273                                   White          NaN   \n",
       "8963814                                   White          NaN   \n",
       "8968341                                   White          NaN   \n",
       "8968877                                   White          NaN   \n",
       "8970580                                   Other  west indian   \n",
       "8971952                                   White          NaN   \n",
       "8976374                                   White          NaN   \n",
       "8976994                                   White          NaN   \n",
       "8977962                                   White          NaN   \n",
       "8978123                                   White          NaN   \n",
       "8982508                                   Asian          NaN   \n",
       "8984036                                   White          NaN   \n",
       "8986182               Black or African American          NaN   \n",
       "8995691                                   White          NaN   \n",
       "8995859                                   White          NaN   \n",
       "8999156                                   White          NaN   \n",
       "\n",
       "        strategy - Topics treatment  valid  \n",
       "1001123               NaN        T3   True  \n",
       "1001888               NaN        T2   True  \n",
       "1004332               NaN        T1   True  \n",
       "1008852               NaN        T1   True  \n",
       "1009339               NaN        T2   True  \n",
       "1009556               NaN        T3   True  \n",
       "1012744               NaN        T1   True  \n",
       "1013582               NaN        T2   True  \n",
       "1019069               NaN        T2   True  \n",
       "1020947               NaN        T1   True  \n",
       "1022969               NaN        T3   True  \n",
       "1025406               NaN        T2   True  \n",
       "1034992               NaN        T3   True  \n",
       "1035488               NaN        T2   True  \n",
       "1038138               NaN        T3   True  \n",
       "1038378               NaN        T1   True  \n",
       "1043506               NaN        T3   True  \n",
       "1044313               NaN        T2   True  \n",
       "1045417               NaN        T1   True  \n",
       "1052729               NaN        T3   True  \n",
       "1052959               NaN        T3   True  \n",
       "1058756               NaN        T1   True  \n",
       "1058900               NaN        T2   True  \n",
       "1060092               NaN        T3   True  \n",
       "1066093               NaN        T1   True  \n",
       "1068815               NaN        T2   True  \n",
       "1073711               NaN        T1  False  \n",
       "1074289               NaN        T4   True  \n",
       "1075064               NaN        T3   True  \n",
       "1075722               NaN        T1   True  \n",
       "...                   ...       ...    ...  \n",
       "8912039               NaN        T1   True  \n",
       "8915831               NaN        T2   True  \n",
       "8924767               NaN        T2   True  \n",
       "8926768               NaN        T3   True  \n",
       "8928657               NaN        T3   True  \n",
       "8930123               NaN        T2   True  \n",
       "8935588               NaN        T1   True  \n",
       "8940115               NaN        T2  False  \n",
       "8946401               NaN        T1   True  \n",
       "8946697               NaN        T1   True  \n",
       "8949788               NaN        T4   True  \n",
       "8953783               NaN        T4   True  \n",
       "8955564               NaN        T2   True  \n",
       "8957763               NaN        T4   True  \n",
       "8961273               NaN        T3   True  \n",
       "8963814               NaN        T2   True  \n",
       "8968341               NaN        T4   True  \n",
       "8968877               NaN        T3   True  \n",
       "8970580               NaN        T3   True  \n",
       "8971952               NaN        T2   True  \n",
       "8976374               NaN        T2   True  \n",
       "8976994               NaN        T1   True  \n",
       "8977962               NaN        T1   True  \n",
       "8978123               NaN        T2   True  \n",
       "8982508               NaN        T2   True  \n",
       "8984036               NaN        T2   True  \n",
       "8986182               NaN        T1   True  \n",
       "8995691               NaN        T4   True  \n",
       "8995859               NaN        T3   True  \n",
       "8999156               NaN        T1   True  \n",
       "\n",
       "[2500 rows x 39 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def calculate_bonus(data,mTurkCode):\n",
    "    try:\n",
    "        actual_bonus = 1\n",
    "        treatment = None\n",
    "        treatments = ['T1_q','T2_q','T3_q','T4_q']\n",
    "        for t in treatments:\n",
    "            if ~np.isnan(float(data[mTurkCode][t])):\n",
    "                actual_bonus-= float(data[mTurkCode][t])\n",
    "                treatment = t[0:2]\n",
    "        return actual_bonus, treatment\n",
    "    except:\n",
    "        print('error in', mTurkCode)\n",
    "        print(data[mTurkCode])\n",
    "\n",
    "for userId in list(data.keys()):\n",
    "    reported_bonus = float(data[userId]['attention_check'])\n",
    "    actual_bonus, treatment = calculate_bonus(data,userId)\n",
    "    data[userId]['treatment'] = treatment\n",
    "    data[userId]['valid'] = False\n",
    "    actual_bonus = round(actual_bonus, 1)\n",
    "    reported_bonus = round(reported_bonus,1)\n",
    "    #if they got the attention correct\n",
    "    if actual_bonus== reported_bonus:\n",
    "        data[userId]['valid'] = True\n",
    "df = pd.DataFrame.from_dict(data,orient='index')\n",
    "#new_df = new_df[new_df.valid==True]\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Coding the gender from free text to 'male' or 'female'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def text_to_gender(x):\n",
    "    try:\n",
    "        x = ''.join(x.split()).lower()\n",
    "        if \"female\" in x or x == \"f\" or 'wo' in x or 'fe' in x or x == 'femaile' or x =='fl':\n",
    "            return \"female\"\n",
    "        elif x == \"male\" or x == \"m\" or x =='mal' or x =='man' or\\\n",
    "        x =='malr' or x == 'mail' or x == 'males' or x == 'utahmale' or x =='males' or x[0:4]=='male' or x=='maine':\n",
    "            return \"male\"\n",
    "        else:\n",
    "            #print(x)\n",
    "            return 'other'\n",
    "    except Exception as ex:\n",
    "        #print(x,ex,'error')\n",
    "        return 'not reported'\n",
    "df['gender'] = df['sex'].apply(text_to_gender)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating 'contribution' column\n",
    "<p>From qualtrics, each condition has its own contribution column .. For ease of analysis, we should have 1 column called 'contribution' and that's it</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['contribution'] = 0\n",
    "df['T1_q'] = df['T1_q'].fillna(0).astype(float)\n",
    "df['T2_q'] = df['T2_q'].fillna(0).astype(float)\n",
    "df['T3_q'] = df['T3_q'].fillna(0).astype(float)\n",
    "df['T4_q'] = df['T4_q'].fillna(0).astype(float)\n",
    "df['contribution'] = df['T1_q']+df['T2_q']+df['T3_q']+df['T4_q']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rename 'Duration (in seconds)' to 'duration_seconds'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['duration_seconds'] = df['Duration (in seconds)'] \n",
    "del df['Duration (in seconds)'] "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Count how many other platforms each participant is part of\n",
    "<p> This actually requires some manual work .. Mostly, users misspelt Prolific and this required fixing by looking at the unique platform names, and making sure to merge the misspelt ones</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:14: FutureWarning: set_value is deprecated and will be removed in a future release. Please use .at[] or .iat[] accessors instead\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "platforms_occurances = []\n",
    "df['n_plaforms'] = 0\n",
    "for indx,participant in df.iterrows():\n",
    "    try:\n",
    "        try:\n",
    "            platforms = list(filter(None, participant.otherPlatforms.split(',')))\n",
    "        except:\n",
    "            platforms = []\n",
    "        if 'Others' in platforms: platforms.remove('Others')\n",
    "        try:\n",
    "            additionalPlatforms = list(filter(None, participant.otherPlatforms_6_TEXT.split(',')))\n",
    "        except:\n",
    "            additionalPlatforms = []\n",
    "        df.set_value(indx, 'n_plaforms', len(additionalPlatforms) + len(platforms))\n",
    "\n",
    "        platforms_occurances += additionalPlatforms\n",
    "    #platforms_occurances += \n",
    "    except:\n",
    "        print('error')\n",
    "        print(indx,participant)\n",
    "        #break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Encode race"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['encoded_race'] = df['race']\n",
    "fig, ax = plt.subplots()\n",
    "df['race'].value_counts().plot(ax=ax, kind='bar')\n",
    "\n",
    "mask = ~(df['encoded_race'].isin(['White','Asian','Black or African American',\n",
    "                                  'White Asian','White Hispanic','Hispanic']))\n",
    "column_name = 'encoded_race'\n",
    "df.loc[mask, column_name] = 'Others'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a238fe630>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "df['encoded_race'].value_counts().plot(ax=ax, kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Encode income (from 0 to 9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 7, 0, 3, 8, 1, 4, 9, 6, 2, nan], dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#income is saved is Q32 in Qualtrics\n",
    "df['incomeCategory'] = df.Q32\n",
    "incomeCategories = ['under $5,000',\n",
    "                   '$5,000 - $10,000',\n",
    "                   '$10,001 - $15,000',\n",
    "                   '$15,001 - $25,000',\n",
    "                   '$25,001 - $35,000',\n",
    "                   '$35,001 - $50,000',\n",
    "                   '$50,001 -  $65,000',\n",
    "                   '$65,001 - $80,000',\n",
    "                   '$80,001 - $100,000',\n",
    "                   'Over $100,000']\n",
    "lvl = 0\n",
    "for incomeCategory in incomeCategories:\n",
    "    mask = df['incomeCategory'] == incomeCategory\n",
    "    column_name = 'incomeCategory'\n",
    "    df.loc[mask, column_name] = lvl\n",
    "    lvl+=1\n",
    "df.incomeCategory.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Encode Education (from 0 to 6) where JD, MD & PHD are coded as 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 4, 2, 3, 6, 1, 0, nan], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['educationCategory'] = df.education\n",
    "educationCategories = ['Less than high school degree',\n",
    "                    'High school graduate',\n",
    "                    \"Some college but no degree\",\n",
    "                    'Associate degree in college (2-year)',\n",
    "                    \"Bachelor's degree in college (4-year)\",\n",
    "                    \"Master's degree\",\n",
    "                    \"Professional degree (JD, MD)\",\n",
    "                    \"Doctoral degree\"]\n",
    "lvl = 0\n",
    "for educationCategory in educationCategories:\n",
    "    mask = df['educationCategory'] == educationCategory\n",
    "    column_name = 'educationCategory'\n",
    "    df.loc[mask, column_name] = lvl\n",
    "    if educationCategory != \"Professional degree (JD, MD)\":\n",
    "        lvl+=1\n",
    "df.educationCategory.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Experience on MTurk from year (i.e., 2016) to duration (i.e., 1 year)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.workerDuration = 2017-df.workerDuration.astype(float)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save file as it is ready for analysis now"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('./data.csv',sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['StartDate', 'EndDate', 'Status', 'IPAddress', 'Progress', 'Finished',\n",
       "       'RecordedDate', 'ResponseId', 'RecipientLastName', 'RecipientFirstName',\n",
       "       'RecipientEmail', 'ExternalReference', 'LocationLatitude',\n",
       "       'LocationLongitude', 'DistributionChannel', 'UserLanguage', 'consent_q',\n",
       "       'T1_q', 'T2_q', 'T3_q', 'T4_q', 'attention_check',\n",
       "       'expecting_from_other', 'otherPlatforms', 'otherPlatforms_6_TEXT',\n",
       "       'workerDuration', 'strategy', 'experimentAbout', 'location', 'age',\n",
       "       'sex', 'education', 'Q32', 'race', 'race_6_TEXT', 'strategy - Topics',\n",
       "       'treatment', 'valid', 'gender', 'contribution', 'duration_seconds',\n",
       "       'n_plaforms', 'encoded_race', 'incomeCategory', 'educationCategory'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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